Monday, June 29, 2026
Temporal Information Retrieval And Question Answering in the Age of LLMs
Presenters: Bhawna Piryani, Avishek Anand and Adam Jatowt
Out-of-distribution Generalized Generative AI
Presenters: Xin Wang, Yuwei Zhou, Zirui Pan and Wenwu Zhu
Towards a Responsible Web: Economic Perspectives on Fairness in Information Retrieval
Presenters: Chen Xu, Clara Rus, Yuanna Liu, Marleen de Jonge, Jun Xu and Maarten de Rijke
LLM & Agents for Recommendation Systems
Keerthi Gopalakrishnan (Walmart Global Tech), Qi Xu (Meta AI), Aysenur Inan (Walmart Global Tech), Zhigang Hua (Meta AI), Shuang Yang (Meta AI), Luyi Ma (Walmart Global Tech)
https://llmandagents4recsys.github.io/
About: Recommendation systems are undergoing a major shift from traditional centralized pipelines to agentic ecosystems that can plan, reason, negotiate, and interact across the entire journey of discovery, personalization, and fulfillment. This workshop explores architectures, evaluation, trust, fairness, and real-world deployments to shape the next generation of adaptive, explainable recommendation ecosystems.
- LLM-augmented Hybrid Recommendation System for Structured Classification of Customs Commodity Descriptions
- GALRec: Aligning Graph with Large Language Model for Sequential Recommendation
- Smart Book Seeker: Agent-Augmented Retrieval System for Metadata-Sparse Libraries
- Ethical Decision-Making under Moral Uncertainty
- Triple Modality Fusion: Aligning Visual, Textual, and Graph Data for LLM-based Multi-Behavior Recommender Systems
- AID: Hypothesis-Grounded Probing for Conversational Recommendation
- LLMs as Orchestrators: Constraint-Compliant Multi-Agent Optimization for Recommendation Systems
- RobustExplain: Evaluating Robustness of LLM-Based Explanation Agents for Recommendation
- Campaign-2-PT-RAG: LLM-Guided Semantic Product Type Attribution for Scalable Campaign Ranking
- TCR: A Trust-Aligned Text-Only Cross-Attention Ranker Distilling Multimodal LLM Reasoning for Recommendation Agents
- SCORE: Story Coherence and Retrieval Enhancement for AI Narratives
Emerging Trends in Web Advertising
Ehsan Toreini (Samsung R&D Institute UK), Muadh Al Kalbani (Samsung R&D Institute UK)
https://samsunginternet.github.io/webads26/
About: The landscape of web advertising is undergoing a profound transformation, fueled by advancements in technologies that prioritize user privacy, AI-driven personalization, and immersive experiences. This workshop provides a platform for timely, responsible discussions among experts from advertising, privacy, data science, and related fields.
- Towards Automated Brand-Safety Detection: A Novel Dataset and Comparative Analysis of Language Models
- Feedback Control for Small Budget Campaigns in Advertising
- Calculating Narrative Tension for Ad Placement in Online Narrative Fiction
- Anatomy of Generative Scam Campaigns in Online Advertising Ecosystems
- Smart Fast Finish: Preventing Overdelivery via Daily Budget Pacing at DoorDash
Zero-knowledge Proof and Blockchain for Web 4.0: Advancing the Post-quantum and Decentralized Era
Shiho Kim (Yonsei University), Roberto Di Pietro (KAUST), Davor Svetinovic (Khalifa University, UAE), KyungHi Chang (Inha University), Madhusudan Singh (Pennsylvania State University)
About: ZABAPAD focuses on zero-knowledge technologies, blockchain infrastructure, and post-quantum readiness for the emerging Web 4.0 ecosystem. Topics include ZKP-based authentication, ZKML, Layer-2 proving/verification, TEE+ZK integration for verifiable compute, and post-quantum migration of identities, wallets, ledgers, and protocols across finance, mobility, healthcare, and AI/ML domains.
- Economics Model for Federated LLM Training via Blockchain
- Hadamard-Aware Bit-wise PIM Architecture via Butterfly Adder-Tree Reuse
- A Taxonomy-Driven Cryptographic Dependency Inventory for Post-Quantum Migration in Decentralized Systems: Triage Rules and a Worked Example
- Verifiable Dropout: Turning Randomness into a Verifiable Claim
- Trustless Feedback: Preserving Privacy and Integrity in Crowdsourced RLHF via Zero-Knowledge Proofs
- Blind-QEM: A Privacy-Preserving Framework for Quantum Error Mitigation via Zero-Knowledge Proofs
- PAC to the Future: Zero-Knowledge Proofs of PAC Private Systems
- SoK: Zero-Knowledge Proof Systems — An Empirical and Theoretical Comparison of SNARKs and STARKs
- Decentralized Video Provenance at the Edge: Blockchain-Assisted Integrity for Security Camera Streams
- Statistical Analysis of 12V Power Load Uncertainty Using Conditional Probability for SDV Energy Management
- ZK-V: Zero-Knowledge Verification for Trustworthy Autonomous Driving Simulation
- A USIM-less Identity Authentication System based on Zero-Knowledge Proofs
- Blockchain-Enabled, W3C Standards-Compliant Decentralized Zero-Knowledge Proof Framework for Mobile Identity Authentication
- Learning-Based Optimization of Atomic Arbitrage in Decentralized Financial Systems
- Spatial Discretization for Fine-Grain Zone Checks with STARKs
- Now or Never: Continuous Surveillance AIoT System for Ephemeral Events in Intermittent Sensor Networks
Graph-enhanced LLMs for Trustworthy Web Data Management
Gianluca Bonifazi (Marche Polytechnic University), Stefano Cirillo (University of Salerno), Eliana Pastor (Polytechnic University of Turin), Luca Virgili (Marche Polytechnic University)
https://glow-workshop.github.io/www2026/
About: This workshop explores synergies between LLMs and graph-based knowledge representations (knowledge graphs, property graphs) to build trustworthy data-driven Web applications. LLMs generate fluent responses but often struggle with factuality, bias, and hallucinations. Graphs provide structured, interconnected representations that can serve as grounding and validation layers for LLM-based systems.
- SMART: Spatio-Temporal Attention-based Large Language Model for Real-Time Traffic Prediction
- Incorporating Graph-Constrained RAG Pipeline for Medicine data
- Incorporating Graph-Constrained RAG Pipeline for Medicine data
- ConceptFormer: Towards Graph-Native Grounding of Large Language Models via Latent Concept Injection
- Better Negatives, Better Predictions: Negative Sample Selection Strategies for Enhancing Biomedical KG Edge Classification
- (wt) GC-DPG: Graph-Constrained Dual-Phase Generation for Safe and Verifiable Chinese Medical Question Answering
- ReGA: Zero-Overhead Graph Alignment for Structural Hallucination Detection Without Generation
- Reasoning in Trees: Improving Retrieval-Augmented Generation for Multi-Hop Question Answering
International Workshop on Trustworthy Multimodal Learning for Social Media Analysis
Jingwei Sun (ByteDance), Guosheng Lin (Nanyang Technological University), Fengmao Lv (Southwest Jiaotong University), Tao Liang (ByteDance), Junlin Fang (Southwest Jiaotong University)
https://ttthhl.github.io/www2026-workshop/
About: TML 2026 focuses on trustworthy multimodal learning methods for social media analysis, covering multimodal social media content analysis with LMMs, effective multimodal fusion and information alignment, and performance and safety evaluation of LMMs including quality of generated content, model hallucinations, and vulnerability to adversarial attacks.
- GeoPBR: Multimodal-Guided PBR Material Generation from a Single View
- HGSA: Heterogeneity-Guided Sarcasm Adaptation for Video Sentiment Analysis via Polarity Disentanglement
- Sparse Causal Latent Features for Robust Multimodal Learning under Distribution Shifts
- Evidential Mixture-of-Experts for Sentiment Regression
- PLM: Point-Language Maps for Zero-shot Object Goal Navigation
- Task-Aligned Unlearning for Multimodal Large Language Models
- Unsupervised Multi-Source Causal Feature Selection
- EmoTg: Modeling Social Response to Telegram Posts Using LLM and NLP Features
12th International Smart City Workshop - Data-Driven Smart Cities
Leonidas Anthopoulos (University of Thessaly, Greece), Marijn Janssen (Delft University of Technology), Vishanth Weerakkody (University of Bradford, UK)
https://webandthecity.home.blog/
About: In the era of IoT, AI, and agentic AI integration, cities are being transformed into urban environments that use data as a foundational asset. This workshop explores how the Web supports smart city transformation and how technologies can improve urban decision-making, optimize services, and enhance citizen well-being.
- A Toolset for Modelling Non-Mediated Governance
- Boltzmann Interaction Models with Gibbs Decision Policies in Multi-Agent Delivery Systems
- LLM-Enabled Participatory Platforms for People-Centric Smart Cities
- Super-Resolution of Urban Socioeconomic Indicators via Graph-Based Recommender Systems
- Closed-Loop Intelligence Architectures for Data-Driven Smart Cities
- A Contrastive Learning and Prompt-Driven Framework for Low-Resource User Geolocation
- Big Data and AI in Smart City Negotiations: A Literature Review
The 2nd International Workshop on Spatio-Temporal Data Mining from the Web
Yuxuan Liang (HKUST Guangzhou), Hao Xue (University of New South Wales), Ming Jin (Griffith University), Fei Wang (Institute of Computing Technology, CAS), Shirui Pan (Griffith University), Flora Salim (University of New South Wales)
https://webst2026.netlify.app/
About: A comprehensive workshop catering to professionals interested in sensing, mining, and understanding big and heterogeneous spatio-temporal data generated from the Web (social media posts, geotagged images, mobility traces) to tackle real-world challenges such as climate change, disaster response, urban planning, and location-based social networks.
1st Workshop on Applied AI and Multimodal Visualization Technologies
Cesar Sanin (Australian Institute of Higher Education / University of New England), Edward Szczerbicki (University of Newcastle / Gdansk University of Technology), Md Rafiqul Islam (Charles Darwin University)
https://rafiqulislamcse24.wixsite.com/aaimvt-26
About: A full-day interactive workshop exploring how applied AI and multimodal visualization technologies can enhance knowledge representation, decision-making, and human-machine collaboration. Topics include cutting-edge research at the intersection of AI and multimodal visualization, interdisciplinary dialogue between researchers and practitioners, and methodologies to improve human decision-making through multimodal data representation.
- VOICY: A Privacy-Centric Modular Architecture for Zero-Shot Voice Cloning and Fine-Tuned Speech Synthesis
- Bridging the Semantic Gap: A Homonym-Aware Ontology Platform for Cybersecurity Interoperability
- Spatial-Temporal Inference of Indoor RSSI and CQI for 3D Coverage Mapping using Dynamic Graph Attention Networks
- Viet Medi Species 2026: A Web-Accessible Multilingual Dataset for Vietnamese Medicinal Biodiversity
- Robust Harmful Meme Detection under Missing Modalities via Shared Representation Learning
Quantum-Safe, Efficient, and AI-Enhanced Blockchains for the Web: A Cooperative Tutorial on Quantum Computing, Blockchain Applications, and Data Standards
Presenters: Dongping Liu, Aoyu Zhang and Luyao Zhang
Bandits, LLMs, and Agentic Web
Presenters: Djallel Bouneffouf and Raphael Feraud
Unstructured to Structured: Building Knowledge Graphs from Documents for Web Applications
Presenters: Qiang Sun, Yihao Ding, Sirui Li and Wei Liu
LLM & Agents for Recommendation Systems
Keerthi Gopalakrishnan (Walmart Global Tech), Qi Xu (Meta AI), Aysenur Inan (Walmart Global Tech), Zhigang Hua (Meta AI), Shuang Yang (Meta AI), Luyi Ma (Walmart Global Tech)
https://llmandagents4recsys.github.io/
About: Recommendation systems are undergoing a major shift from traditional centralized pipelines to agentic ecosystems that can plan, reason, negotiate, and interact across the entire journey of discovery, personalization, and fulfillment. This workshop explores architectures, evaluation, trust, fairness, and real-world deployments to shape the next generation of adaptive, explainable recommendation ecosystems.
- LLM-augmented Hybrid Recommendation System for Structured Classification of Customs Commodity Descriptions
- GALRec: Aligning Graph with Large Language Model for Sequential Recommendation
- Smart Book Seeker: Agent-Augmented Retrieval System for Metadata-Sparse Libraries
- Ethical Decision-Making under Moral Uncertainty
- Triple Modality Fusion: Aligning Visual, Textual, and Graph Data for LLM-based Multi-Behavior Recommender Systems
- AID: Hypothesis-Grounded Probing for Conversational Recommendation
- LLMs as Orchestrators: Constraint-Compliant Multi-Agent Optimization for Recommendation Systems
- RobustExplain: Evaluating Robustness of LLM-Based Explanation Agents for Recommendation
- Campaign-2-PT-RAG: LLM-Guided Semantic Product Type Attribution for Scalable Campaign Ranking
- TCR: A Trust-Aligned Text-Only Cross-Attention Ranker Distilling Multimodal LLM Reasoning for Recommendation Agents
- SCORE: Story Coherence and Retrieval Enhancement for AI Narratives
Emerging Trends in Web Advertising
Ehsan Toreini (Samsung R&D Institute UK), Muadh Al Kalbani (Samsung R&D Institute UK)
https://samsunginternet.github.io/webads26/
About: The landscape of web advertising is undergoing a profound transformation, fueled by advancements in technologies that prioritize user privacy, AI-driven personalization, and immersive experiences. This workshop provides a platform for timely, responsible discussions among experts from advertising, privacy, data science, and related fields.
- Towards Automated Brand-Safety Detection: A Novel Dataset and Comparative Analysis of Language Models
- Feedback Control for Small Budget Campaigns in Advertising
- Calculating Narrative Tension for Ad Placement in Online Narrative Fiction
- Anatomy of Generative Scam Campaigns in Online Advertising Ecosystems
- Smart Fast Finish: Preventing Overdelivery via Daily Budget Pacing at DoorDash
Zero-knowledge Proof and Blockchain for Web 4.0: Advancing the Post-quantum and Decentralized Era
Shiho Kim (Yonsei University), Roberto Di Pietro (KAUST), Davor Svetinovic (Khalifa University, UAE), KyungHi Chang (Inha University), Madhusudan Singh (Pennsylvania State University)
About: ZABAPAD focuses on zero-knowledge technologies, blockchain infrastructure, and post-quantum readiness for the emerging Web 4.0 ecosystem. Topics include ZKP-based authentication, ZKML, Layer-2 proving/verification, TEE+ZK integration for verifiable compute, and post-quantum migration of identities, wallets, ledgers, and protocols across finance, mobility, healthcare, and AI/ML domains.
- Economics Model for Federated LLM Training via Blockchain
- Hadamard-Aware Bit-wise PIM Architecture via Butterfly Adder-Tree Reuse
- A Taxonomy-Driven Cryptographic Dependency Inventory for Post-Quantum Migration in Decentralized Systems: Triage Rules and a Worked Example
- Verifiable Dropout: Turning Randomness into a Verifiable Claim
- Trustless Feedback: Preserving Privacy and Integrity in Crowdsourced RLHF via Zero-Knowledge Proofs
- Blind-QEM: A Privacy-Preserving Framework for Quantum Error Mitigation via Zero-Knowledge Proofs
- PAC to the Future: Zero-Knowledge Proofs of PAC Private Systems
- SoK: Zero-Knowledge Proof Systems — An Empirical and Theoretical Comparison of SNARKs and STARKs
- Decentralized Video Provenance at the Edge: Blockchain-Assisted Integrity for Security Camera Streams
- Statistical Analysis of 12V Power Load Uncertainty Using Conditional Probability for SDV Energy Management
- ZK-V: Zero-Knowledge Verification for Trustworthy Autonomous Driving Simulation
- A USIM-less Identity Authentication System based on Zero-Knowledge Proofs
- Blockchain-Enabled, W3C Standards-Compliant Decentralized Zero-Knowledge Proof Framework for Mobile Identity Authentication
- Learning-Based Optimization of Atomic Arbitrage in Decentralized Financial Systems
- Spatial Discretization for Fine-Grain Zone Checks with STARKs
- Now or Never: Continuous Surveillance AIoT System for Ephemeral Events in Intermittent Sensor Networks
4th International Workshop on AI and Semantic Technologies for the Scientific, Technical, and Legal Web
Rima Dessi (Higher College of Technologies, UAE), Jeenu Joy (FIZ-Karlsruhe), Danilo Dessi (University of Sharjah, UAE), Francesco Osborne (The Open University, UK), Hidir Aras (FIZ-Karlsruhe)
https://semtech4stld.github.io/
About: SemTech 2026 focuses on methods combining Semantic Web technologies, NLP, LLMs, and other AI to model knowledge across scientific, technical, and legal domains. The workshop invites research on knowledge graph creation, semantic annotation, LLM-KG hybrid reasoning, and trustworthy AI pipelines for scientific, patent, and legal Web content.
- The LOPE Method: Improving Consistent Property Extraction for Scientific Knowledge Graphs Using LLMs
- ORKG Properties Ontology Consolidated: LLM-Driven Refinement of Crowdsourced Knowledge for Machine-Actionability
- Beyond the Rules: Understanding the Design Logic of Internet Standards
- The Atomic Instruction Gap: Instruction-Tuned LLMs Struggle with Simple, Self-Contained Directives
- Saliency-Guided Embedding Alignment for Query-to-Document Legal Case Retrieval
Third International Workshop on Prompt Engineering for Pre-Trained Language Models
Damien Graux (EcoVadis), Sebastien Montella (Huawei Technologies Ltd.), Hajira Jabeen (UniKlinik Cologne)
https://prompteng-ws.github.io/2026/
About: This workshop gathers practitioners to exchange about good practices, optimizations, results and novel paradigms for designing efficient prompts and context-building to make use of LLMs. Since LLM performances are highly dependent on the exact phrasing used in prompts, the workshop focuses on fail-retry strategies, prompt optimization, and novel prompting paradigms.
6th International Workshop on Computational Methods for Online Discourse Analysis
Stefan Dietze (Heinrich-Heine-University Dusseldorf & GESIS), Dimitar Dimitrov (GESIS), Pavlos Fafalios (Technical University of Crete & FORTH-ICS), Konstantin Todorov (University of Montpellier / LIRMM / CNRS)
https://beyondfacts2026.wordpress.com/
About: This workshop strengthens relations between knowledge representation and NLP communities, providing a forum for works on modeling, extraction and analysis of online discourse. It addresses the need for shared understanding of discourse data—claims, arguments, stances, and veracity—using methods from machine learning, NLP, large language models and Web data mining.
The 2nd International Workshop on Social Science Meets Web Data: Reproducible and Reusable Computational Approaches
Fakhri Momeni (GESIS), Arnim Bleier (GESIS), Danilo Dessi (University of Sharjah, UAE), Muhammad Taimoor Khan (GESIS)
https://sites.google.com/view/r2cass/home
About: R2CASS advances computational reproducibility in social science, which relies on digital behavioral data from social media platforms. It brings together computer scientists, social scientists, and policy makers to improve the credibility and reproducibility of computational social science research. Features a hands-on session on the Methods Hub platform for computational reproducibility.
- From Code to Executable Method: Making Your Code Both Methods Hub and MyBinder Ready
- Who Shapes Web Standards? Uncovering the Main Topics of Interest in the W3C
- The Verification Crisis: Expert Perceptions of GenAI Disinformation and the Case for Reproducible Provenance
- Automating Computational Reproducibility in Social Science: Comparing Prompt-Based and Agent-Based Approaches
- Social Bias Benchmarks for Large Language Models
Tuesday, June 30, 2026
Next-Gen Code Development with Collaborative AI Agents
Presenters: Shweta Garg, Behrooz Omidvar-Tehrani, Shengyu Fu, Gauthier Guinet and Baishakhi Ray
Conversational Search: From Fundamentals to Frontiers in the Age of Agents
Presenters: Chuan Meng, Fengran Mo, Mohammad Aliannejadi, Jeff Dalton and Jian-Yun Nie
Foundations for the Agentic Web: Infrastructure, Economics, and Society
Presenters: Ramesh Raskar and Pradyumna Chari
The 2nd Workshop on Human-Centered Recommender Systems
Kaike Zhang (University of Chinese Academy of Sciences), Jiakai Tang (Renmin University of China), Julian McAuley (University of California, San Diego), Lina Yao (CSIRO Data61, Australia), and others
About: HCRS calls for a paradigm shift from optimizing engagement toward designing recommender systems that truly understand, involve, and benefit people. Centered around Human Understanding, Human Involvement, and Human Impact, the workshop covers topics from LLM-based interactive recommenders to societal welfare optimization and responsible recommendation research.
- Post-Training Fairness Control: A Single-Train Framework for Dynamic Fairness in Recommendation
- RecoWorld: Building Simulated Environments for Agentic Recommender Systems
- STCRank: Spatio-temporal Collaborative Ranking for Interactive Recommender System at Kuaishou E-shop
- Fairness at a Glance: Can We Audit Model Fairness Before Training Completes?
- Orthogonal Meta-learning Boosted Bayesian Optimization for Uncertain Multi-Objective Recommendation
- Evaluating LLM Recommendations Under Stress
- Beyond Engagement: A Human-Centered Evaluation Framework for LLM-Powered Recommender Systems
- Knowledge Graph Editing Model for Enhancing Recommendation Systems
- Learning to Alleviate Familiarity Bias in Video Recommendation
Joint Workshop on Diffusion of Harmful Content on Online Web and Countering Misinformation in the Age of LLMs and Agents
Thomas Mandl (University of Hildesheim), Haiming Liu (University of Southampton), Gautam Kishore Shahi (University of Duisburg-Essen), Amit Kumar Jaiswal (IIT BHU Varanasi), and others
https://dhow-workshop.github.io/2026/
About: DHOW-MiLLA consolidates research on harmful content diffusion and misinformation under one umbrella. With LLMs and agent-based AI systems creating a dual-use paradigm, this workshop focuses on cross-platform, multilingual solutions that mitigate modern misinformation while harnessing AI capabilities for verification, fact-checking, and detection of deepfakes, propaganda, and multimodal disinformation.
- Deception Factories: Industrial-Scale Cloaking in Harmful Synthetic Media
- RAMA: Retrieval-Augmented Multi-Agent Framework for Misinformation Detection in Multimodal Fact-Checking
- ToxiTwitch: Toward Emote-Aware Hybrid Moderation for Live Streaming Platforms
- Context-Aware Silhouette-Based Age Estimation for Child Sexual Abuse Material (CSAM) Detection
- On VLMs for Diverse Tasks in Multimodal Meme Classification
- An Interpretable Agentic Framework for Multimodal Hate Video Analysis with Explicit Evidence Attribution
- From Generation to Detection: Leveraging Empirically Derived Linguistic Hints for LLM-Based Fake News Detection
- Exploring the Domain Sensitivity of AI Chatbots in Correcting Misinformation
- Beyond Detection: An Epistemic Limit of Purely Computational Misinformation Defense
- Exploring the Domain Sensitivity of AI Chatbots in Correcting Misinformation
- Amplified Adversarial Vulnerabilities in Multi-Agent LLM Systems Despite Safety Tuning
- Trustworthy or Just Lucky? Composite Trust Scoring for Behavioral Evaluation of LLM Agents
International Workshop on Foundations and Architectures for the Agentic Web
Abderrahmane Maaradji (University of Doha for Science and Technology), Boualem Benatallah (Dublin City University), Fatma Outay (Zayed University, UAE), Ramesh Raskar (MIT Media Lab), Pradyumna Chari (MIT Media Lab), and others
About: The Agentic Web is emerging as billions of AI agents discover, communicate, and coordinate across the open Web. This workshop covers web-native building blocks: agent registries, identity and credentials (DIDs/VCs), authorization (OAuth 2.0), discovery (DNS-SD), and federation patterns, as well as economic mechanisms (reputation, knowledge pricing) and societal coordination (governance, accountability).
- Real-Time Procedural Learning From Experience for AI Agents
- SemaReg: Semantic Service Registry for Resilient IoTWorkflow Orchestration in Edge Computing Environments
- On the Economic and Governance Mechanisms for the Agentic Web: A Global South Perspective
- An Agentic System for Automated Polymer Property Prediction in Low-Code Environments
- An Agentic System for Automated Polymer Property Prediction in Low-Code Environments
- Can Large Language Models Govern Themselves? A Technical, Ethical, and Governance Perspective
- A Prompt-Aware Structuring Framework for Reliable Reuse of AI-Generated Content in the Agentic Web
- WAB: Overcoming Memory, Network, and Security Walls in Native Agentic Browsers with WebAssembly
- How to Measure Node Importance in the Agentic Web
- NANDA: Resolution, Discovery, and Governance for the Agentic Web
The 16th Temporal Web Analytics Workshop
Marc Spaniol (University of Caen Normandy), Omar Alonso (Amazon), Ricardo Baeza-Yates (KTH, Royal Institute of Technology Stockholm)
About: TempWeb provides a venue for researchers across all domains where the temporal dimension opens new challenges and possibilities. The workshop focuses on investigating infrastructures, scalable methods, and innovative software for aggregating, querying, and analyzing heterogeneous temporal data at Internet scale.
- SLS: A Scalable Logic Subgraph Framework for Temporal Web Analytics and Hybrid Search
- Scalable Anomaly Detection for Temporal Web Streams via Approximate Nearest Neighbor Search
- Community-Preserving Temporal Graph Backboning via Joint Spectral Analysis of Laplacians
- The State of the Internet: Insights from Security Indicators
- MiningWeb Evolution: A Dataset of DOM Changes Across Websites
- ImVision: Adapting Pretrained Vision Models for Time-Series Imputation
- Using Psycholinguistic Features for Multiplex Community Detection in Temporal Social Networks
- PerQA: A Benchmark for Temporally Sensitive Questions on Heterogeneous Personal Data
- Benchmarking Temporal Web3 Intelligence: Lessons from the FinSurvival 2025 Challenge
- Suicide Risk Prediction via Comment‑Influenced Mental State Trajectories
- Temporal Challenges in Data-Driven Scenario-Building for Climate-Neutral Cities
2nd International Workshop on Transformative Insights in Multi-faceted Evaluation
Lei Wang (Griffith University & CSIRO), Md Zakir Hossain (Curtin University), Tom Gedeon (Curtin University), Syed Mohammed Shamsul Islam (ECU), Rafiqul Islam (Charles Sturt University), Yasmeen George (Monash University), Shreya Ghosh (University of Queensland)
https://time.griffith.edu.au/workshop/time2026/
About: TIME brings together domain experts to share insights on social network analysis, graph algorithms, web mining, semantics, security, privacy, fairness, and ethics on the web. The workshop invites survey, evaluation, or review papers that critically analyze models and datasets from diverse perspectives, complemented by invited talks from experts and industry leaders.
- Fine-Grained Visual Understanding for Multimodal and Trustworthy AI
- Decentralised Trust Layers for the Web: Towards Transparent AI-Powered Platforms
- Beyond Fine-Tuning: The Present and Future of Parameter-Efficient Fine-Tuning in Vision Transformers
- RadioAR: Autoregressive Modeling for Accurate Radio Map Estimation
- Evaluating Trustworthiness in Reactive Web Architectures: A Structured Framework and Comparative Analysis
- Rethinking Object Detection and Tracking
- An Edge Computing Framework for Deep Learning-Based Anomaly Detection in Satellite-Linked Autonomous Vehicles
- Privacy-Aware Machine Unlearning with SISA for Reinforcement Learning–Based Ransomware Detection
- How Quantum Period Finding Breaks Rivest Shamir Adleman Algorithms
- Guided Path Sampling: Steering Diffusion Models Back on Track with Principled Path Guidance
- Towards Better Evaluation Metrics for Text-to-Motion Generation
- Graph Aggregation Beyond Homophily Assumption: a more meaningful way to model networks
- Talking-Head Generation in Practice
- Feasibility of Cryptography In a Blockchain-Enhanced ICS Security
- Orchestrating Heterogeneous Experts: A Scalable MoE Framework with Anisotropy-Preserving Fusion
- Measuring Privacy Risks and Tradeoffs in Financial Synthetic Data Generation
4th Workshop on Augmented Intelligence in Technology-Assisted Review Systems (ALTARS 2026)
Giorgio Maria Di Nunzio (University of Padova, Italy), Evangelos Kanoulas (University of Amsterdam), Prasenjit Majumder (DAIICT, Gandhinagar, India)
https://altars2026.dei.unipd.it/
About: ALTARS 2026 explores recent advances and open challenges in Technology-Assisted Review (TAR) systems for large-scale, high-recall retrieval across the Web. Topics include intelligent retrieval, human-in-the-loop learning, explainable and responsible AI, and the integration of LLMs and knowledge graphs into review workflows across legal, scientific, and web-scale domains.
- Early Recall Estimation and Stopping in Technology-Assisted Reviews via Ranker-Sampler Fusion
- Deep GraphRAG: A Balanced Approach to Hierarchical Retrieval and Adaptive Integration
- Train Large-Use Small: Optimizing within the Theoretical Limits of Embedding-based Retrieval
- Towards Automating Articles Screening Processes Using Chain-of-Thought Large Language Models
International Workshop on Federated Foundation Models for the Web 2026
Irwin King (The Chinese University of Hong Kong), Guodong Long (University of Technology Sydney), Zenglin Xu (Fudan University), Han Yu (Nanyang Technological University), Xiaoli Tang (Nanyang Technological University)
https://federated-learning.org/fl@fm-www-2026/
About: With foundation models becoming the norm in ML development, federated learning (FL) becomes crucial for privacy-preserving and distributed learning at scale. This workshop provides a platform for researchers and industry professionals to discuss latest advancements in FL methods for foundation models, enabling efficient training while safeguarding sensitive data.
Trustworthy Foundation Models for Web Intelligence: Causal Perspectives and Challenges
Haoang Chi (Tsinghua University), Qi Wang (Tsinghua University), Jiantong Jiang (University of Melbourne), Jiangchao Yao (Shanghai Jiaotong University), Feng Liu (University of Melbourne), Bo Han (Hong Kong Baptist University)
https://www-tfm-causal.github.io/www2026-workshop/
About: This workshop advances discussion on Trustworthy Foundation Models for the Web by introducing a causal perspective to improving the reliability, interpretability, and fairness of large-scale models. It convenes experts from machine learning, causal inference, web data mining, and social computing to establish a roadmap toward more robust, transparent, and ethically aligned Web AI systems.
- Eroding the Truth-Default: A Causal Analysis of Human Susceptibility to Foundation Model Hallucinations and Disinformation in the Wild
- LLM and AI Agent: Golden Rule is All We Need
- Hierarchical Prompt Contrastive Learning for Weakly Supervised Histopathology Segmentation
- TRACE: Transparent Web Reliability Assessment with Contextual Explanations
- Multi-Branch Cooperation Networks for Enhanced Click-Through Rate Prediction in Large-Scale E-Commerce Search
- Struggling at the Start: Structural Causes of Decoding Difficulty in Code Generation
- Prediction Guardian: A Distribution-based Real-time Anomaly Detection and Mitigation Framework for Online Advertising
LLM-Enhanced Web-Centric Spatio-Temporal Intelligence: Methods, Applications, and Frontier Research
Presenters: Zijian Zhang, Hao Miao, Yuxuan Liang, Yan Zhao and Irwin King
Generalist Model for Structured Data: Foundations, Frontiers and Applications
Presenters: Peng Cui, Xingxuan Zhang, Han-Jia Ye, Jintai Chen and Shuyang Li
Robust Graph Learning on the Web: Challenges, Methods, and Applications
Presenters: Xiang Ao, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng and Qing He
Responsible Prompting on the Web: Governance, Mini-Evaluation, and Readiness with ChatGPT
Presenters: Manali Sharma and Ayush Garg
Joint Workshop on Diffusion of Harmful Content on Online Web and Countering Misinformation in the Age of LLMs and Agents
Thomas Mandl (University of Hildesheim), Haiming Liu (University of Southampton), Gautam Kishore Shahi (University of Duisburg-Essen), Amit Kumar Jaiswal (IIT BHU Varanasi), and others
https://dhow-workshop.github.io/2026/
About: DHOW-MiLLA consolidates research on harmful content diffusion and misinformation under one umbrella. With LLMs and agent-based AI systems creating a dual-use paradigm, this workshop focuses on cross-platform, multilingual solutions that mitigate modern misinformation while harnessing AI capabilities for verification, fact-checking, and detection of deepfakes, propaganda, and multimodal disinformation.
- Deception Factories: Industrial-Scale Cloaking in Harmful Synthetic Media
- RAMA: Retrieval-Augmented Multi-Agent Framework for Misinformation Detection in Multimodal Fact-Checking
- ToxiTwitch: Toward Emote-Aware Hybrid Moderation for Live Streaming Platforms
- Context-Aware Silhouette-Based Age Estimation for Child Sexual Abuse Material (CSAM) Detection
- On VLMs for Diverse Tasks in Multimodal Meme Classification
- An Interpretable Agentic Framework for Multimodal Hate Video Analysis with Explicit Evidence Attribution
- From Generation to Detection: Leveraging Empirically Derived Linguistic Hints for LLM-Based Fake News Detection
- Exploring the Domain Sensitivity of AI Chatbots in Correcting Misinformation
- Beyond Detection: An Epistemic Limit of Purely Computational Misinformation Defense
- Exploring the Domain Sensitivity of AI Chatbots in Correcting Misinformation
- Amplified Adversarial Vulnerabilities in Multi-Agent LLM Systems Despite Safety Tuning
- Trustworthy or Just Lucky? Composite Trust Scoring for Behavioral Evaluation of LLM Agents
International Workshop on Foundations and Architectures for the Agentic Web
Abderrahmane Maaradji (University of Doha for Science and Technology), Boualem Benatallah (Dublin City University), Fatma Outay (Zayed University, UAE), Ramesh Raskar (MIT Media Lab), Pradyumna Chari (MIT Media Lab), and others
About: The Agentic Web is emerging as billions of AI agents discover, communicate, and coordinate across the open Web. This workshop covers web-native building blocks: agent registries, identity and credentials (DIDs/VCs), authorization (OAuth 2.0), discovery (DNS-SD), and federation patterns, as well as economic mechanisms (reputation, knowledge pricing) and societal coordination (governance, accountability).
- Real-Time Procedural Learning From Experience for AI Agents
- SemaReg: Semantic Service Registry for Resilient IoTWorkflow Orchestration in Edge Computing Environments
- On the Economic and Governance Mechanisms for the Agentic Web: A Global South Perspective
- An Agentic System for Automated Polymer Property Prediction in Low-Code Environments
- An Agentic System for Automated Polymer Property Prediction in Low-Code Environments
- Can Large Language Models Govern Themselves? A Technical, Ethical, and Governance Perspective
- A Prompt-Aware Structuring Framework for Reliable Reuse of AI-Generated Content in the Agentic Web
- WAB: Overcoming Memory, Network, and Security Walls in Native Agentic Browsers with WebAssembly
- How to Measure Node Importance in the Agentic Web
- NANDA: Resolution, Discovery, and Governance for the Agentic Web
The 16th Temporal Web Analytics Workshop
Marc Spaniol (University of Caen Normandy), Omar Alonso (Amazon), Ricardo Baeza-Yates (KTH, Royal Institute of Technology Stockholm)
About: TempWeb provides a venue for researchers across all domains where the temporal dimension opens new challenges and possibilities. The workshop focuses on investigating infrastructures, scalable methods, and innovative software for aggregating, querying, and analyzing heterogeneous temporal data at Internet scale.
- SLS: A Scalable Logic Subgraph Framework for Temporal Web Analytics and Hybrid Search
- Scalable Anomaly Detection for Temporal Web Streams via Approximate Nearest Neighbor Search
- Community-Preserving Temporal Graph Backboning via Joint Spectral Analysis of Laplacians
- The State of the Internet: Insights from Security Indicators
- MiningWeb Evolution: A Dataset of DOM Changes Across Websites
- ImVision: Adapting Pretrained Vision Models for Time-Series Imputation
- Using Psycholinguistic Features for Multiplex Community Detection in Temporal Social Networks
- PerQA: A Benchmark for Temporally Sensitive Questions on Heterogeneous Personal Data
- Benchmarking Temporal Web3 Intelligence: Lessons from the FinSurvival 2025 Challenge
- Suicide Risk Prediction via Comment‑Influenced Mental State Trajectories
- Temporal Challenges in Data-Driven Scenario-Building for Climate-Neutral Cities
2nd International Workshop on Transformative Insights in Multi-faceted Evaluation
Lei Wang (Griffith University & CSIRO), Md Zakir Hossain (Curtin University), Tom Gedeon (Curtin University), Syed Mohammed Shamsul Islam (ECU), Rafiqul Islam (Charles Sturt University), Yasmeen George (Monash University), Shreya Ghosh (University of Queensland)
https://time.griffith.edu.au/workshop/time2026/
About: TIME brings together domain experts to share insights on social network analysis, graph algorithms, web mining, semantics, security, privacy, fairness, and ethics on the web. The workshop invites survey, evaluation, or review papers that critically analyze models and datasets from diverse perspectives, complemented by invited talks from experts and industry leaders.
- Fine-Grained Visual Understanding for Multimodal and Trustworthy AI
- Decentralised Trust Layers for the Web: Towards Transparent AI-Powered Platforms
- Beyond Fine-Tuning: The Present and Future of Parameter-Efficient Fine-Tuning in Vision Transformers
- RadioAR: Autoregressive Modeling for Accurate Radio Map Estimation
- Evaluating Trustworthiness in Reactive Web Architectures: A Structured Framework and Comparative Analysis
- Rethinking Object Detection and Tracking
- An Edge Computing Framework for Deep Learning-Based Anomaly Detection in Satellite-Linked Autonomous Vehicles
- Privacy-Aware Machine Unlearning with SISA for Reinforcement Learning–Based Ransomware Detection
- How Quantum Period Finding Breaks Rivest Shamir Adleman Algorithms
- Guided Path Sampling: Steering Diffusion Models Back on Track with Principled Path Guidance
- Towards Better Evaluation Metrics for Text-to-Motion Generation
- Graph Aggregation Beyond Homophily Assumption: a more meaningful way to model networks
- Talking-Head Generation in Practice
- Feasibility of Cryptography In a Blockchain-Enhanced ICS Security
- Orchestrating Heterogeneous Experts: A Scalable MoE Framework with Anisotropy-Preserving Fusion
- Measuring Privacy Risks and Tradeoffs in Financial Synthetic Data Generation
The Workshop on Adverse Impacts and Collateral Effects of Artificial Intelligence Technologies
Esma Aimeur (Universite de Montreal), Rim Ben Salem (Polytechnique Montreal), Dorsaf Sallami (Universite de Montreal), Julita Vassileva (University of Saskatchewan), Nora Boulahia-Cuppens (Polytechnique Montreal)
https://sites.google.com/view/aiofai-2026/home
About: AiOfAi highlights the double-edged nature of AI in the digital age, examining how it can be exploited to undermine trust, privacy, and integrity, while also serving as a foundation for more secure, ethical, and resilient digital ecosystems. The workshop discusses the societal impact of widespread AI adoption, ethical and legal frameworks for responsible AI deployment, and emerging approaches in cybersecurity and fairness.
- Prompt Scene Investigation: Uncovering the Evidence in LLMs
- DEMO: Ontology-Based Automated Security Analysis for AI Systems and Applications
- Industrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital Ecosystems
- Age Classification in Child Sexual Abuse Materials
- The More You Say, the More You Risk: Ethical Concerns in Large Language Model Reasoning Frameworks
- The Agentic Insider: Redefining Insider Threats Beyond Human Actors in Autonomous AI Systems
- Assessing the Reliability of Persona-Conditioned LLMs as Synthetic Survey Respondents
Fourth International Workshop on Multimodal Content Analysis for Social Good
Usman Naseem (Macquarie University), Surendrabikram Thapa (Virginia Tech), Roy Ka-Wei Lee (Singapore University of Technology and Design), Mehwish Nasim (University of Western Australia)
https://sites.google.com/view/mm4sg-webconf26
About: MM4SG addresses the challenge of moderating multimodal content (memes, text-embedded images) on social platforms. The workshop brings together researchers from NLP, machine learning, computational social science, and ethics to explore innovative solutions for content moderation, sharing cutting-edge research on multimodal content analysis techniques.
- Multimodal Content Analysis for Social Good
- Concept-Grounded Detection of Vaccine Misinformation in Multimodal Content Using Interpretable Vision-Language Models
- UniSafe: Modality-Agnostic Hateful Content Detection via Shared-Space Projection
- Frugal Agents: Efficient Bio Reasoning via Long-Sequence Compression and Prompt-Gated Memory
- Fair Geolocation Extraction from Humanitarian Documents Using Large Language Models
- From Code to Rubrics: A Multimodal Evaluation of LLM Systems for Automated Feedback Generation
- MAF-GAN: Modality-Aware Fusion GAN for Multimodal Fake News Detection
- Multimodal Deployment Risks in Manufacturing AI: A Survey of Boundary Failures, Taxonomy, and Governance in Industry 5.0
- Fed-S2: Adversarially Disentangled Federated Multimodal RAG for Safety-Critical Long-Tail Fault Diagnosis
- No Evidence, No Problem: When Less is More for Out of Context Multimodal Misinformation Detection
- Do You Think What I Think? A Qualitative Study for Maximising User Engagement through Latent Visual Properties
- Exploring the Influence of Lifestyle, Social Health, and Demographic Factors on Psychological Well-being and Engagement Levels
- Can Thinking Models Think to Detect Hateful Memes?
- Semi-supervised Instruction Tuning for Large Language Models on Text-Attributed Graphs
- Analyzing the Impact of Image Novelty and Text Emotion on Meme Engagement
- Mixture of Orthogonal Decomposition for Semantically Generalisable Multimodal Deepfake Detection with Deepfake Manifold Disentanglement
Wednesday, July 1, 2026
- Topology-Aware Feature Sorting Enables Universal Modeling on Homophilic and Heterophilic Graphs
- A Graph Foundation Model for Unified Anomaly Detection
- RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation
- Towards Graph Foundation Model: Node Feature Transfer Invariant Modeling on General Graphs
- GraphRAG-R1: Graph Retrieval-Augmented Generation with Process-Constrained Reinforcement Learning
- Unsupervised Subgraph Anomaly Detection based on Pattern Collaboration
- DP-DGAD: A Generalist Dynamic Graph Anomaly Detector with Dynamic Prototypes
- Anomaly Detection of Interaction Behaviors in Streaming Graphs
- PAGE: Progressive Anomaly Generation Network for Semi-supervised Graph Anomaly Detection
- Cross-Type Semantic Alignment for Multi-Type Anomaly Detection in Heterogeneous Graphs
- QuiZSF: A Retrieval-Augmented Framework for Zero-Shot Time Series Forecasting
- SDR-CIR: Semantic Debias Retrieval Framework for Training-Free Zero-Shot Composed Image Retrieval
- FlowRAG: Continual Learning for Dynamic Retriever in Retrieval-Augmented Generation
- DA-RAG: Dynamic Attributed Community Search for Retrieval-Augmented Generation
- HyperRAG: Reasoning N-ary Facts over Hypergraphs for Retrieval Augmented Generation
- Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model
- Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts?
- Matrix as Plan: Structured Logical Reasoning with Feedback-Driven Replanning
- GraphCogent: Mitigating LLMs' Working Memory Constraints via Multi-Agent Collaboration in Complex Graph Understanding
- Large Language Model for OWL Proofs
- FedBridge: Accelerating Edge-Assisted Federated Learning for Model-Heterogeneous Clients
- WinFLoRA: Incentivizing Client-Adaptive Aggregation in Federated LoRA under Privacy Heterogeneity
- Beyond Class Boundaries: Federated Visual Primitive Sharing with Text-Guided Adaptation
- CoLOR-DP: Conjugate Low-Rank Differential Privacy for Structure-Aware LoRA Fine-Tuning
- CA-PFL: Client-adaptive Parameter-efficient Fine-tuning for Personalized Federated Learning
- Reading Between the Lines: Towards Reliable Black-box LLM Fingerprinting via Zeroth-order Gradient Estimation
- Forge: A Robust Multi-tab Website Fingerprinting Attack via Blind Source Separation
- HiFi-WF: Toward Realistic Website Fingerprinting with Multi-tab and Subpage Recognition
- RoFiRe: Robust Website Fingerprinting on Real-World Tor Traffic via Improved Augmentation and Normalization
- Understanding Server-side Commercial Fingerprinting
- A Frequency-Aware Mixture of Heterogeneous Experts Framework for Knowledge Tracing
- Efficient High-Dimensional Time Series Forecasting with Transformers: A Channel Reordering Perspective
- Modeling Point-to-Point Dependency for High-Dimensional Long-Term Series Forecasting
- Time-TK: A Multi-Offset Temporal Interaction Framework Combining Transformer and Kolmogorov-Arnold Networks for Time Series Forecasting
- FedDis: A Causal Disentanglement Framework for Federated Traffic Prediction
- ThinkRec: Thinking-based recommendation via LLM
- Iterative Semantic Reasoning from Individual to Group Interests for Generative Recommendation with LLMs
- Reinforcement Learning-Constrained Segmented User Modeling with Large Language Models for Recommendation
- Multi-Task Multi-Behavior Sequential Recommendation
- RMBRec: Robust Multi-Behavior Recommendation towards Target Behaviors
- FRiskGPT: A Generative Foundation Model for Financial Risk Detection
- VeritasFi: An Adaptable, Multi-tiered RAG Framework for Multi-modal Financial Question Answering
- When Agents Trade: Live Multi-Market Trading Arena for LLM Agents
- Financial Wind Tunnel: A Retrieval-Augmented Market Simulator
- FishFlow: A LLM-Empowered Dynamic Pricing Framework for Online Fleamarket Platform
- Hierarchical Semantic RL: Tackling the Problem of Dynamic Action Space for RL-based Recommendations
- Beyond the Flat Sequence: Hierarchical and Preference-Aware Generative Recommendations
- NEZHA: A Zero-sacrifice and Hyperspeed Decoding Architecture for Generative Recommendations
- OneTrans: Unified Feature Interaction and Sequence Modeling with One Transformer in Industrial Recommender
- GRADE: Personalized Multi-Task Fusion via Group-Relative Reinforcement Learning with Adaptive Dirichlet Exploration
- STIndex: A Context-Aware Multi-Dimensional Spatiotemporal Information Extraction System
- SJBP: A Platform to Launch a Novel Jailbreak Attack on Large Language Models Based on Content's Spatial Distribution
- Pattern Discovery with Wide-Lens Analysis and Sharp-Focus Validation
- DualMind: Towards Understanding Cognitive-Affective Cascades in Public Opinion Dissemination via Multi-Agent Simulation
- RISE: A Retrieval-Augmented Generation Enhanced Immersive System for Education
- PromptX: A Cognitive Agent Platform with Long-term Memory
- TrustResearcher: Automating Knowledge-Grounded and Transparent Research Ideation with Multi-Agent Collaboration
- Multimodal Peer Review Simulation with Actionable To-Do Recommendations for Community-Aware Manuscript Revisions
- DOS: Dual-Flow Orthogonal Semantic IDs for Recommendation in Meituan
- RASTP: Representation-Aware Semantic Token Pruning for Generative Recommendation with Semantic Identifiers
- Few-shot and Zero-shot Audience Expansion with User and Task Model Pre-training on Tabular Data
- Learning To Generate Effective Health Advertisements
- Decentralized in Name Only: The Centralization of DAO Labor
- A Reinforcement Learning Based Hyper-Parameter Generation System Guided by LLM-Powered Virtual Users
- DualGR: Generative Retrieval with Long and Short-Term Interests Modeling
- Cascaded Verification Framework: A Progressive Approach for Mitigating Hallucinations in Large Language Models
- Hidden-in-Plain-Text: A Benchmark for Social-Web Indirect Prompt Injection in RAG
- Activation Caching for Retrieval-Augmented Generation
- PH-EMO: Decoding Emotions from the Brain Inward – EEG-Grounded Multimodal Reasoning with LLMs
- GPR: Empowering Generation with Graph-Pretrained Retriever
- Graph Discrete Prompt Optimization for Knowledge Graph Question Answering
- Improving the Accuracy of Community Detection on Signed Networks via Community Refinement and Contrastive Learning
- AIMER: Affective Intention-guided Multimodal Emotion Reasoner for Visual Emotion Analysis in Social Media
- SIR-Teach: Student-Implicit Reward Teaching
- Generative Retrieval for E‑commerce: Jointly Learning Embedding and Codebook with Same Product Cluster
- Rethink Web Service Resilience in Space: A Radiation-Aware and Sustainable Transmission Solution
- Access Controlled Website Interaction for Agentic AI with Delegated Critical Tasks
- Infer As You Train: A Symmetric Paradigm of Masked Generative for Click-Through Rate Prediction
- Learning Probabilistic Distributions for CTR Uncertainty
- Structure Over Scale: Diagnosing Liquidity Fragility in Concentrated-Liquidity AMMs
- Fedivertex: a Graph Dataset based on Decentralized Social Media
- Cost Ratio Aware Algorithm for Representative Subset Selection
- Deterring A Small Collusion is All You Need
- Analysis of CEX-DEX Arbitrage Opportunities with Hidden Markov Models
- LiquidityPool: Game-Theoretic Analysis of Stakeholder Revenue in Ranking-Dependent DeFi
- Allocating Chores with Restricted Additive Costs: Achieving EFX, MMS, and Efficiency Simultaneously
- All-but-one MMS Allocation for Chores
- Barter Exchange with Asymmetric Item Valuations
- Difference-based Sample Selection for Federated Graph Rationalization
- Class-Domain Incremental Learning on Graphs via Disentangled Knowledge Distillation
- Exploring Sequential Dynamics on Temporal Graphs via Composite Filtering
- Maximum Edge-based Quasi-Clique: Novel Iterative Frameworks
- Scalable and Provable Biclique-Preserving Clustering: The Power of Counting-based Approaches
- Graph Diffusion Evolution Model for Multi-Conditional Molecular Generation
- Integrated Mixture of Neighborhood and Community Experts for Graph-Based Fraud Detection
- FeedGuard: Online Critic-Guided Reinforcement Learning with Privacy-Preserving Feedback for Recommendation
- HomeRun: Performing Curveball Trades quasi in Streaming for Fast Null Modeling of Graphs, Hypergraphs, and Binary Matrices
- What Should I Cite? A RAG Benchmark for Academic Citation Prediction
- Med-R$^2$: Crafting Trustworthy LLM Physicians via Retrieval and Reasoning of Evidence-Based Medicine
- Generalized Pseudo-Relevance Feedback
- Rethinking the Hidden Risk of Reranking: Achieving Risk-aware Reranking with Information Gain for RAG with LLMs
- NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains
- Pedestrian-Centric Discriminative and Fine-grained Semantic Mining for Text-based Person Retrieval
- Bridging Expert Reasoning and LLM Detection: A Knowledge-Driven Framework for Malicious Packages
- HingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues
- LHG: LLM-enhanced and Heterogeneous Graph-induced for Unsupervised Social Event Detection
- Decoding Web Memorization: A Semantic Membership Inference Attack on LLMs
- Bridging Semantic Understanding and Popularity Bias with LLMs
- Simple-Sampling and Hard-Mixup with Prototypes to Rebalance Contrastive Learning for Text Classification
- Traceable Latent Variable Discovery Based on Multi-Agent Collaboration
- DyLogNet: A Dynamic Multi-Relational Graph Framework for Log Anomaly Detection
- SIsomap: Secure Collaborative Manifold Learning with Reducing Communication Costs
- PrivSplit: A Lossless Method for Prompt Privacy in Distributed Parameter-Efficient Fine-Tuning
- TGNN: Enhancing Pixel Tracking Detection via LLM-driven Annotation and GAT-powered Structural Representation
- DiSCoQR: Diffusion-Driven Semantic Compression for Robust Image Steganography in Standard QR Codes
- Netting Phish in the IPFS Ocean: Real-Time Monitoring and Characterization of Decentralized Phishing Campaigns
- FraudShield: Knowledge Graph Empowered Defense for LLMs against Fraud Attacks
- HyperDetector: Advanced Persistent Threat Detection via Hypergraph Neural Networks with Enhanced Global Perception
- Privacy-Friendly Adaptation of Vision Transformers for Communication and Latency-Efficient Private Inference
- MGFFD-VLM: Multi-Granularity Prompt Learning for Face Forgery Detection with VLM
- Smaller but Better: Plasticity-Preserving Continual Learning for Embedded AI
- Macro-Micro Collaborative Learning for Logical Data Center Microservice Indicators Forecasting
- Task-Aware Cloud-End Offloading for Vision-Language Model Serving via Dynamic Modality-Specific Adapter Scheduling
- SkyCL: Swift Continuous Learning with Kinship-Awareness for Multi-Drone Video Analytics under Drastic Drift
- Meteor: High-Performance Control Message Delivery for Large-Scale Clouds
- MASI: Memory-Adaptive Inference Framework for Spiking Neural Networks on Edge Devices
- FedRGL: Federated Riemannian Graph Learning in Mixed-Curvature Spaces with Ricci-Gated Convolution
- MoE-LC: General-Purpose Lossless Compression for Multi-modal Data via Entropy-Aware Multi-Experts
- Quantum-enhanced Representation Learning and Matching Learning for Recommendation
- From Entity Reliability to Clean Feedback: An Entity-Aware Denoising Framework Beyond Interaction-Level Signals
- Thorki: Decoupling General and Personalized Knowledge with Collaborative Fusion for Personalized Federated Learning
- Large Language Models-Enhanced Semantic Diffusion for User-Centric Recommendation
- Not All Information Brings Benefits: Personalization-Driven Agent Debate for Conversational Recommendation
- FairFS: Addressing Deep Feature Selection Biases for Recommender System
- Tail-Aware Data Augmentation for Long-Tail Sequential Recommendation
- Off-Policy Learning with Limited Supply
- S2CDR: Smoothing-Sharpening Process Model for Cross-Domain Recommendation
- Multi-view Semantic Contrastive Alignment for Multimodal Recommendation
- pFedDKS: Detached Knowledge Sharing for Personalized Federated Learning
- Adaptive Contrastive Learning in Sequential Recommendation based on Perturbation and Restoration Networks
- EIAN: Explicit Interaction-aware Attention Network for Interpretable Event Modeling
- Cardinality is Not Enough: Super Host Detection via Segmented Cardinality Estimation
- Dynamic Prototype-Augmented Stance Detection: Learning from the Seen to Reason about the Unseen
- Triple-R: Iterative Query Rewriting and Refinement for Retrieval-Augmented Fake News Detection
- Expectation-Maximization Driven Contrastive Disentanglement for Generalized Category Discovery
- KMLP: A Scalable Hybrid Architecture for Web-Scale Tabular Data Modeling
- Measuring and Enhancing Human Value Alignment in Zero-Shot Document-Level Claim Extraction
- OpenDigger: A Practical Framework for Assessing Community Health and Sustainability in Open Source Collaboration Platforms
- Bridging Visual Dynamics and Narrative Reasoning: Multimodal Large Language Models for Short Drama Quality Assessment
- Not All Candidates are Created Equal: A Heterogeneity-Aware Approach to Pre-ranking in Recommender Systems
- Unbiased Multimodal Reranking for Long-Tail Short-Video Search
- The Chatbot Knows It’s You: Dialogue Attribution in Unauthenticated Human–LLM Sessions
- Toward Green Computing: General Carbon Intensity Forecasting via Dual Graph Empowered Time Series Foundation Model
- Egocentric Co-Pilot: Web-Native Smart-Glasses Agents for Assistive Egocentric AI
- Green Industrial Engineering on the Web: Agent-Driven Ant Colony Optimization Tuning for Energy-Efficient 3D Pipe Routing
- Dynamic Min-Max Multi-Dimensional Reinforcement Backdoor Attacks and Orchestrated Closed-Loop Defense in Fairness-Aware Web Federated Finance
- MultiHateLoc: Towards Temporal Localisation of Multimodal Hate Content in Online Videos
- 'They've Stolen My GPL-Licensed Model!': Toward Standardized and Transparent Model Licensing
- Community Fact-Checks Do Not Break Follower Loyalty
- Fair and Carbon-Aware LLM Routing for Web Services
- Towards Fair Large Language Model-based Recommender Systems without Costly Retraining
- Enhancing Rare Event Detection via Counterfactual Generation with Exogenous Variables
- coTherapist: A Behavior-Aligned Small Language Model Framework to Support Mental Healthcare Experts
- Debating Truth: Debate-driven Claim Verification with Multiple Large Language Model Agents
- Sustainable and Responsible ECG-Based AI Diagnostics: Masked Frequency Reconstruction with Peak-Aware Transformers
- FairGU: Fairness-aware Graph Unlearning in Social Networks
- Auto-bidding under Return-on-Spend Constraints with Uncertainty Quantification
- DARA: Few-shot Budget Allocation in Online Advertising via In-Context Decision Making with RL-Finetuned LLMs
- LBM: Hierarchical Large Auto-Bidding Model via Reasoning and Acting
- Platform Competition in the Autobidding World
- AHBid: An Adaptable Hierarchical Bidding Framework for Cross-Channel Advertising
- Unveiling Backdoor Propagation in Graphs: Neuron-Centric Defense Mechanisms
- Identification of Influential Node Group in Attributed Graph through Explaining Graph Neural Network
- Can LLMs Fool Graph Learning? Exploring Universal Adversarial Attacks on Text-Attributed Graphs
- A^2GBD: Attack-Agnostic Graph Backdoor Defense
- Towards Robust Heterogeneous Graph Explanations under Structural Perturbations
- Difficulty-Aware Agentic Orchestration for Query-Specific Multi-Agent Workflows
- Toward Generalized Web Agent Training: A Deep Dive into Entropy-Balanced Reinforcement Learning
- QChunker: Learning Question-Aware Text Chunking for Domain RAG via Multi-Agent Debate
- DeepAgent: A General Reasoning Agent with Scalable Toolsets
- Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs
- EMSEdit: Efficient Multi-Step Meta-Learning-based Model Editing
- CASE: Conflict-assessed Knowledge-sensitive Neuron Tuning for Lifelong Model Editing
- RAIE:Region-Aware Incremental Preference Editing with LoRA for LLM-based Recommendation
- Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs
- WiNELL: Wikipedia Never-Ending Updating with LLM Agents
- FedSRD: Sparsify-Reconstruct-Decompose for Communication-Efficient Federated Large Language Models Fine-Tuning
- Personalized Federated Fine-Tuning for LLMs via Data-Driven Heterogeneous Model Architectures
- EcoTune: Edge-Cloud Collaborative Model Adaptation for Budget-Constrained On-Device SLM Personalization
- FedDiG: Frequency-Guided Diffusion Diversity for Generalizable Federated Time Series Classification
- FedAKD: Federated Adaptive Knowledge Distillation via Global Knowledge Calibration and Decoupling
- Unveiling and Mitigating Untargeted Poisoning Attacks on Federated Knowledge Graph Embedding
- Reconstructing Training Data from Adapter-based Federated Large Language Models
- Xemis: Fair and Robust Privacy-Preserving Data Trading based on Distributed Noise Sharing
- Federated Latent Factor Learning for Privacy-Preserving Spatio-Temporal Signal Recovery
- Beyond Denial-of-Service: The Puppeteer's Attack for Fine-Grained Control in Ranking-Based Federated Learning
- Hermes the Polyglot: A Unified Framework to Enhance Expressiveness for Multimodal Interlingual Subtitling
- BHGap: A Deep Iterative Prompting and Multi-stage Alignment Framework for Dynamic Facial Expression Recognition
- MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues
- CCAF: Coarse-to-fine Cross-Modal Alignment and Fusion for Multimodal Sentiment Analysis
- ATGFB-MFF: Adaptive Text-Guided Fiber Bundle Feature Fusion with LLMs for Multimodal Sentiment Analysis and Emotion Recognition in Conversations
- Generative Data Transformation: From Mixed to Unified Data
- WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging
- SemaCDR: LLM-Powered Transferable Semantics for Cross-Domain Sequential Recommendation
- The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation
- Gaussian Mixture Flow Matching with Domain Alignment for Multi-Domain Sequential Recommendation
- DiffGRM: Diffusion-based Generative Recommendation Model
- Modeling Endogenous Logic: Causal Neuro-Symbolic Reasoning Model for Explainable Multi-Behavior Recommendation
- MCLMR: A Model-Agnostic Causal Learning Framework for Multi-Behavior Recommendation
- C-HyPOD: Causal Hyperbolic Learning with Prototype Orthogonal Disentanglement for Graph Out-of-Distribution Recommendation
- Causality Enhancement for Cross-Domain Recommendation
- PI2I: A Personalized Item-Based Collaborative Filtering Retrieval Framework
- AliBoostV2: CTR-Growth Balanced Boosting Framework in Billion-Scale Recommendation Platform
- BanditLP: Large-Scale Stochastic Optimization for Personalized Recommendations
- Unleashing the Potential of Sparse Attention on Long-term Behaviors for CTR Prediction
- Improving Multi Task Recommendations via Cross User Learning with a Hybrid Pointwise and Pairwise Ranking Loss
- Lang2Plan: An LLM-Powered Multi-Agent System for Building Layout Planning
- NGCAPTCHA: A CAPTCHA Bridging the Past and the Future
- G-SEIR: A Graph-Enhanced Epidemic Forecasting System for Dengue Intervention
- SAMPLE: A Spatial/Channel-wise Attention GCN with MLP and Periodic Linear Encoding for Land Boundary Demarcation System
- A Large Language Model-based Agent for Automated Machine Learning Workflow Construction
- Deep Research Comparator: A Platform For Fine-grained Human Annotations of Deep Research Agents
- Docs2Synth: A Synthetic Data Tuned Retriever Framework for Documents Understanding
- GCAgent: Enhancing Group Chat Communication through Dialogue Agents System
- Let It Try First: Uncertainty-Guided Retrieval Switching for Retrieval-Augmented Question Answering
- DiffusionGS: Generative Search with Query Conditioned Diffusion in Kuaishou
- LLM Reasoning for Cold-Start Item Recommendation
- Hierarchical Layer Attention with Contrastive Learning for Robust Audio Deepfake Detection
- Online Bidding Algorithms with Strict Return on Spend (ROS) Constraint
- OMGRec: One-time Matching-based Generative Rerank with Permutation-level Modeling in E-commerce
- LPEdit: Locality-Preserving Knowledge Editing for MultiModal Large Language Models
- Img2KG: Ontology-Driven Correction of Visual Triples
- A Life‑Cycle Assessment of the Hidden Environmental Cost of Selfies
- We May Not Need Much Visual Encoding of Web Data for Question Answering
- CityVerse: A Unified Data Framework for Evaluating Large Language Models in Urban Computing
- An Improved Combinatorial Algorithm for Edge-Colored Clustering in Hypergraphs
- BitHeteroNet: A Heterogeneous Network Benchmark for Enhanced Anomaly Detection in Bitcoin Transactions
- Feature-PI: A Data Repository for Learning-based Feature Importance Estimation
- BiCare: Bi-Objective Set Similarity with Box Embeddings for Safe and Effective Healthcare Decision Support
- ReMi-ReMath: A Reverse-Mutual Reasoning Framework for Enhancing Mathematical Thinking in Small Language Models
- Beyond Isolated Clients: Integrating Graph-Based Embeddings into Event Sequence Models
- GlotWeb: Web Indexing for Minority Languages
- Graph Poisoning for Node Rank Manipulation
- P-Aligner: Pre-Aligning LLMs via Principled Instruction Synthesis
- Interaction-level Membership Inference Attack for Recommender Systems via Cluster-based User Modeling
- CytoCrowd: A Multi-Annotator Benchmark Dataset for Cytology Image Analysis
- FilterRec: An Intent-Aware Framework for Dynamic Filter Recommendation
- MCP vs RAG vs NLWeb vs HTML: A Comparison of the Effectiveness and Efficiency of Different Agent Interfaces to the Web
- SIT-KGED: Simply Inject Topology into LLM for Knowledge Graph Error Detection
- Online Rounding and Pricing Schemes for k-Rental Problems
- Online Advertising with Spatial Interactions
- Automated Deterministic Auction Design with Objective Decomposition
- The Query Complexity of Uniform Pricing
- Determinants and Effects of Buy Box Suppression on Amazon
- Additively Competitive Secretaries
- Improving the Price of Anarchy via Predictions in Parallel-Link Networks
- TAWRMAC: A Novel Dynamic Graph Representation Learning Method
- negMIX: Negative Mixup for OOD Generalization in Open-Set Node Classification
- UTAG: Leveraging LLM as a Unified Embedding Generator for Text-Attributed Graphs
- Mitigating Dynamic Graph Distribution Shifts via Mixture of Variational Experts
- Text-attributed Graph Condensation via Text Selection and Attribute Matching
- Practical Group Steiner Tree Algorithms for Web Applications with Many Groups
- GraphTARIF: Linear Graph Transformer with Augmented Rank and Improved Focus
- VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection
- Sustained Vertex Cover on Temporal Graphs
- Dual-level Reweighting for Positive-Unlabeled Graph Classification
- Dual-Branch Multi-Granularity Network with Structured Contrastive Ranking for Cross-Modal Retrieval
- Less is More: Compact Clue Selection for Efficient Retrieval-Augmented Generation Reasoning
- Déjà Vu of Strange Stickers! Enhancing Out-of-Distribution Robustness in Sticker Retrieval via Cross-Modal Intent Alignment
- SQL-Checker: Error Detection and Labeling for Text-to-SQL with Interpretability Analysis
- To Search or Not to Search: Aligning the Decision Boundary of Deep Search Agents via Causal Intervention
- XR: Cross-Modal Agents for Composed Image Retrieval
- Lifting Manifolds to Mitigate Pseudo-Alignment in LLM4TS
- MePe: Rethinking Multimodal Chinese Idiom Reading Comprehension from a Metaphorical Perspective
- PLIKD: Prompt Learning with Instance-aware Knowledge Distillation for Web-scale Semantic Image Classification
- Neuro-Sym Supporter: A Thoughtful Emotion Support Agent Integrating Neural and Symbolic Policy Learning
- LoSemB: Logic-Guided Semantic Bridging for Inductive Tool Retrieval
- Beyond Factual Queries: A Novel Predictive Retrieval-Augmented Generation
- Generalized Incremental Learning under Concept Drift across Evolving Data Streams
- Red-Teaming Privacy-Protective Perturbations: Blind Face Restoration as an Attack Strategy
- LLMQuA: Practical Backdoor Injection on Large Language Model Quantization
- Unveiling the Vulnerability of Graph-LLMs: An Interpretable Multi-Dimensional Adversarial Attack on TAGs
- Robust LLM-Based Website Fingerprinting under Dynamic Real-World Conditions
- Breaking Cross-modal Alignment in Embodied Intelligence: A Multimodal Adversarial Attack Framework for Vision-Language-Action Models
- TGweaver: Synthesizing Transaction Graphs for De-anonymization Analysis
- Towards Practical LLM Unlearning: Efficient, Modular, and Retain-Free
- The Promise vs. Reality of NFT Decentralization: An Empirical Study of Storage Strategies and Defects
- PWAVEP: Purifying Imperceptible Adversarial Perturbations in 3D Point Clouds via Spectral Graph Wavelets
- Zelda: Feedback-driven Closed-box Fuzzing for Identifying Web Application Vulnerabilities
- TraceLLM: Evaluating and Exploring Large Language Models on Trace Analysis in Microservice-based Web Applications
- Broken Promise: Differential Analysis of Functional Discrepancies Between WebAssembly and Native Binaries
- Self-Speculative Decoding for On-device MoE Acceleration
- HeteroSim: Towards High-Fidelity Heterogeneous LLM Training Simulation on GPUs
- Curiosity Driven Knowledge Retrieval for Mobile Agents
- Prototype Augmentation-based Edge-end Heterogeneous Collaborative Learning
- Octopus: Vehicle-to-Road Collaborative Perception for Autonomous Driving with Closed-Loop Fusion
- Optimizing Multi-Turn Interactive Recommendation Agents via Generative Intrinsic Motivation
- Unveiling and Simulating Short-Video Addiction Behaviors via Economic Addiction Theory
- PRISM: Personalized Recommendation via Information Synergy Module
- Learning on Adaptive Manifolds for Graph Collaborative Filtering
- Room Matters: Dynamic Room-level Collaboration Information Modeling for Live Streaming Recommendation
- ONE-PASS: Single Forward Pass Decoding for Listwise Reranking
- Personalized Learning Path Planning through Goal-Driven Learner State Modeling
- Bridging Time and Domains: A Time-aware Framework for Cross-Domain Sequential Recommendation
- CC-OR-Net: A Unified Framework for LTV Prediction through Structural Decoupling
- KE-FedRS: Tackling Data Sparsity in Federated Recommendation via Knowledge Enhancement
- Long Story Short: Auditing U.S. Political Polarization in Recommendations for Long- vs. Short-form Videos on YouTube
- Thinking Bidirectionally: A Reasoning and Self-Correction Approach for Text-Based Event Prediction with Large Language Models
- Hyperbolic Multimodal Generative Representation Learning for Generalized Zero-Shot Multimodal Information Extraction
- MIDE: Multimodal Dialogue Emotion Recognition via Mutual Information Enhancement and Dynamic Modality Selection
- GFMixer: Decoupled Temporal Gradient and Fourier-Aware Attention for Time Series Forecasting
- MIGC-CMamba: Cross-Domain Mamba with Multi-Scale Imaging and Granular-Ball Computing for Traffic Flow Prediction
- STaR: Towards Effective and Stable Table Reasoning via Slow-Thinking Large Language Models
- Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning
- GPU-accelerated Multi-relational Parallel Graph Retrieval for Web-scale Recommendations
- Accurate and Efficient Personalized Query Rewriting in Baidu Search
- PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations
- A Creator-Aware Recommendation System for Content Platforms
- Spiking Graph Predictive Coding for Reliable OOD Generalization
- Boosting Large Language Models for Mental Manipulation Detection via Data Augmentation and Distillation
- ReRule: Temporal Rule-Augmented Language Modeling for Causal Event Chain Completion
- IndicAG: An Explainable Agentic Framework for Indic-Multilingual Multidimensional Aggression Detection
- GRAND: A Robust Diffusion Framework for Multi-Granularity Graph Anomaly Detection in Web Platforms
- Accurate Trajectory Recovery in Underserved Areas via Location Inference from Web Crowdsourced Data
- Modeling Multimodal Information Cascade on Social Media with Interpretable Mixture of Experts
- TheraMind: A Strategic and Adaptive Agent for Longitudinal Psychological Counseling
- When Ads Become Profiles: Uncovering the Invisible Risk of Web Advertising at Scale with LLMs
- TravelReasoner: Leveraging Large Reasoning Models to Address Mobility Data Gap
- Longitudinal Trends in Global Climate Change Discourse on Facebook
- Bowling with ChatGPT: On the Evolving User Interactions with Conversational AI Systems
- Invisible Walls in Cities: Designing LLM Agent to Predict Urban Segregation Experience with Social Media Content
- How Green Is Your Login? A Cross-Protocol Benchmark of Authentication Energy & Latency
- MultiCheck: Strengthening Web Trust with Unified Multimodal Fact Verification
Thursday, July 2, 2026
- PMIScore: An Unsupervised Approach to Quantify Dialogue Engagement
- Strategic Content Creation with GenAI: To Share or Not to Share?
- Pay for The Second-Best Service: A Game-Theoretic Approach against Dishonest LLM Providers
- Position Auctions in AI-Generated Content
- How to Strategize Human Content Creation in the Era of GenAI?
- Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger
- IVQ-GNN: Mitigating Performance Gaps from Graph Connection Pattern Inconsistency via Vector Quantization
- Frequency-Corrupt Based Graph Self-Supervised Learning
- Discrete Diffusion-Based Model-Level Explanation of Heterogeneous GNNs with Node Features
- SliceGX: Layer-wise GNN Explanation with Model-slicing
- Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning
- Beyond Single-Granularity Prompts: A Multi-Scale Chain-of-Thought Prompt Learning for Graph
- Riemannian Graph Tokenizer for Structural Knowledge Transfer
- LEDA: Latent Semantic Distribution Alignment for Multi-domain Graph Pre-training
- Towards A Universal Graph Structural Encoder
- CompactRAG: Reducing LLM Calls and Token Overhead in Multi-Hop Question Answering
- KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation
- Inferential Question Answering
- RPO-RAG: Aligning Small LLMs with Relation-aware Preference Optimization for Knowledge Graph Question Answering
- Multi-Granularity Multi-Modal Knowledge Graph Representation Learning via Subgraph-Aware Adaptive Fusion and Hierarchical Relation Modeling
- Grasp: Refining Semantic Graphs into Purified Knowledge for Cross-Modal Communication
- Enhancing Multi-Modal Entity Alignment via Multi-Grained Decision Fusion
- Relation-Aware Multimodal Analogical Reasoning with Modality Fingerprints and Adaptive Gating
- DyMRL: Dynamic Multispace Representation Learning for Multimodal Event Forecasting in Knowledge Graph
- Wiseswap: Elastic Datacenter Network-Aware Disaggregated Memory for Multi-Tenant Cloud
- LaTune: Lightweight and Adaptive Configuration Tuning for LLM Inference on Edge Devices
- EdgeGen: Efficient LLM-Empowered Model Generation with Quantization-Aware NAS
- BeeQoS: A Cloud-Native QoS System for Adaptive and Scalable Multi-Priority Bandwidth Guarantees
- A Structure-Agnostic Co-Tuning Framework for LLMs and SLMs in Cloud-Edge Systems
- ProvGuard: Logic-Aware Multi-View Contrastive Learning for Robust and Efficient Host Threat Detection
- Re-understanding Graph Unlearning through Memorization
- Towards Robust Detection of Chinese Toxic Variants via Dynamic Knowledge Graph–LLM Reasoning
- When Reasoning Leaks Membership: Membership Inference Attack on Black-box Large Reasoning Models
- Unequal Vulnerability: The Differential Impact of Label Flipping Attacks Across Classes
- PAMAS: Self-Adaptive Multi-Agent System with Perspective Aggregation for Misinformation Detection
- TrueLens: Video Fake News Detection with Dual Level Evidence Gathering and Consolidation
- Is Misinformation More Open? A Study of robots.txt Gatekeeping on the Web
- From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the Wild
- Adaptive Graph Reweighting for Collaborative Filtering
- IACLR: Intention Alignment via Contrastive Learning for Bipartite Graph Recommendation
- PULSE: Socially-Aware User Representation Modeling Toward Parameter-Efficient Graph Collaborative Filtering
- Line Graphs Are Here! Unlock a Simple Solution for Data Sparsity and Class Imbalance in Recommender System
- Multi-modal Bipartite Graph Structure Learning with Information Bottleneck for Micro-video Recommendation
- Self-Evolving LLMs via Continual Instruction Tuning
- Large Reasoning Embedding Models: Towards Next-Generation Dense Retrieval Paradigm
- Probe-and-Fetch: Dynamic KV Cache Pruning for Accelerated Long-Context Inference in Web-Scale AI Search
- DG-MCTS: Dual-Guidance Monte Carlo Tree Search for Adaptive Emotional Support Dialogue Planning
- LaV-CoT: Language-Aware Visual CoT with Multi-Aspect Reward Optimization for Multilingual Text-Centric VQA
- A Generative Contextual Comprehension Paradigm for Takeout Ranking Model
- ARADD: An Automatic Real-World API Discovery and Deployment Framework for AI Guide Service in Baidu Map
- TRABL: A Unified Framework for Travel Domain Aspect-Based Sentiment Analysis Applications of Large Language Models
- From Sold-Out to Sales Uplift: Causal Inference for Intelligent Inventory Management on Online Travel Platforms
- Enhancing Ride-Hailing Forecasting at DiDi with Multi-View Geospatial Representation Learning from the Web
- When to Invoke: Refining LLM Fairness with Toxicity Assessment
- Trust in One Round: Confidence Estimation for Large Language Models via Structural Signals
- BalDRO: A Distributionally Robust Optimization based Framework for Large Language Model Unlearning
- SEP-Attack: A Simple and Effective Paradigm for Transfer-Based Textual Adversarial Attack
- Fine-Grained Traceability for Transparent ML Pipelines
- CiteLLM: An Agentic Platform for Trustworthy Scientific Reference Discovery
- A Framework for Continual Knowledge Graph Embedding
- Roamify: An Interactive Browser Extension for Real-Time LLM-Based Travel Itinerary Generation
- PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing
- DriftNavi: Talk through Your Data Drift with LLMs
- Implementation of a Metacognition Framework for Self-Awareness and Self-Regulation in Ensembles of LLMs
- BaiJia: An Open Role-Playing Platform of Chinese Historical Characters
- LegalKit: A Modular Toolkit for Efficient Legal AI Evaluation
- ReFuGe: Feature Generation for Prediction Tasks on Relational Databases with LLM Agents
- Suppression or Deletion: A Restoration-Based Representation-Level Analysis of Machine Unlearning
- C^2-SFL:Class-Balanced and Cost-Aware Split Federated Learning for Mobile Edge Computing
- SAGE-Prompt: Structured Attribution Guarded Explanation for Explainable Deepfake Question Answering
- Multi-source Multi-level Multi-token Ethereum Dataset and Benchmark Platform
- Is More Context Always Better? Examining LLM Reasoning Capability for Time Interval Prediction
- Beyond Playtesting: A Generative Multi-Agent Simulation System for Massively Multiplayer Online Games
- COINS: Semantic Ids Enhanced Cold Item Representation for Click-through Rate Prediction in E-commerce Search
- AWMA-MoE: Attention-Guided Watermark Adapter with MoE for Latent Diffusion Models
- Towards Responsible Recommendations: A Daily Updated Ranking Model for Content Issue Detection
- ThinkTank-ME: A Multi-Expert Framework for Middle East Event Forecasting
- An 8-Way Taxonomy for Multimodal Disinformation and Detection Benchmark
- DTRec: Learning Dynamic Reasoning Trajectories for Sequential Recommendation
- Machine Learning as a Service (MLaaS) Dataset Generator Framework for IoT Environments
- Explainable Graph Sparsification with Shapley Values
- Coarse-Fine: A Novel VPA Strategy for Boosting Resource Utilization of Transient Offline Tasks
- PAOSC: Plug-and-play Attention Optimization for Semantic Consistency in LLMs
- Breaking Semantic-Aware Watermarks via LLM-Guided Coherence-Preserving Semantic Injection
- Anonymous Linear Bandits for Multi-User Systems
- Efficient Learning of Sparse Representations from Interactions
- Back to the Future: Look-ahead Augmentation and Parallel Self-Refinement for Time Series Forecasting
- CGPT: Cluster-Guided Partial Tables with LLM-Generated Supervision for Table Retrieval
- EDTF: A Plug-and-Play Learning Framework for Estimated Delivery Time Task
- Understanding Post-Exploit Laundering Behavior on Ethereum
- HAUTE: Harmonizing Action Units with Temporal-contextual Embeddings for Deepfake Detection
- Marketing Hosting: From Fixed to Endogenous Budgets
- Efficient and Fair Allocation on Graphs: From Orientation to Position-Aware Valuations
- Data Pricing via Competitive Equilibrium
- Single-Sample Bilateral Trade with a Broker
- Differentially Private Anonymous Bandits for Multi-User Systems
- Understanding Strategic Platform Entry and Seller Exploration: A Stackelberg Model
- Stochastic Wage Suppression on Gig Platforms and How to Organize Against It
- A Unified Graph Clustering Network
- E$^2$SGNN: Reconciling Expression and Efficiency in Spiking Graph Neural Network
- Graph-to-Tree: Topological Decomposition for Self-Supervised Learning
- Revisiting Graph-Level Anomaly Detection: From Partially to Fully Unsupervised Learning
- FedCND: Federated Graph-Level Clustering under Inter-Client Cluster Number Discrepancy
- SCOUT: Structure-Aware Aspect and Anchor-Count Selection for Node Attribute Augmentation via Positional Information
- Breaking the Scalability Barrier in Constrained Graph-Based Networked Control via Decision-Focused Learning
- Invariant Learning on Heterogeneous Graphs via Subgraph Environment Inference
- ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion
- Weighted Graph Clustering via Scale Contraction and Graph Structure Learning
- Are LLM Web Search Engines Sustainable? A Web-Measurement Study of Real-Time Fetching
- A Fact-Checking Framework with Denoising Evidence Retrieval and LLM-Based Debate Verification
- Conflict-Aware RAG: Multi-Stage Learning with Conflict Signals for Robust Retrieval-Augmented Generation
- IRAG: Robust Multimodal Retrieval-Augmented Generation via Hazard Separation
- Towards Open-World Retrieval-Augmented Generation on Knowledge Graph: A Multi-Agent Collaboration Framework
- HL-CMR: Hypergraph Learning for Cross-Modal Retrieval
- MARCH: Multi-Teacher Contrastive Hypergraph Distillation
- Missingness-aware Federated Contrastive Learning on Semantic Graphs
- Adaptive Multi-Interaction Web Semantic Graph Representation
- Counterfactual Augmented Causal Reasoning for Aspect-Based Sentiment Analysis
- S-Path-RAG: Semantic-Aware Shortest-Path Retrieval Augmented Generation for Multi-Hop Knowledge Graph Question Answering
- Harnessing LLM for Noise-Robust Cognitive Diagnosis in Web-Based Intelligent Education Systems
- DTransKT: A Dual Transferable Knowledge Tracing Framework for Cross-Disciplinary Self-Adaptation
- DRMD: Explainable Depression Detection Based on Metaphorical Conceptual Mapping
- Unveiling the Resilience of LLM-Enhanced Search Engines against Black-Hat SEO Manipulation
- Beyond Detection: Autonomous Anomaly Remediation for MCP Against Tool Poisoning Attacks
- On the Effectiveness of Mempool-based Transaction Auditing
- Too Much Sharing, Too Little Security: Authentication Cookie Theft At Scale
- DIARY: Differentially Private Recovery with Adaptive Privacy Budgets in Federated Unlearning
- ShadowClone: Scalable Decentralized Identity with Cross-Domain Anonymity and Accountable Traceability
- DeepUL: Deep Unlearning via Model Sparsity
- DSSmoothing: Toward Certified Dataset Ownership Verification for Pre-trained Language Models via Dual-Space Smoothing
- ARuleCon: Agentic Security Rule Conversion
- ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts
- FSDI: Frequency-Shaped Diffusion For Time-Series Imputation
- Automated Model Selection for Multivariate Time Series Forecasting
- Energy-Efficient and Dequantization-Free Quantization of LLMs: A Spiking Neural Network Approach to Salient Value Mitigation
- Enhancing Federated Class-Incremental Learning via Spatial-Temporal Statistics Aggregation
- Starlink in the Wild: Multi-Perspective Measurements via DNS
- From Prediction to Understanding: Leveraging Reasoning in Large Language Model-based Recommendations
- Generative Regression Based Watch Time Prediction for Short-Video Recommendation
- FeDecider: An LLM-Based Framework for Federated Cross-Domain Recommendation
- Joint Similar User Exploration and Informative Behavior Guidance for Multi-Modal New Item Recommendation
- ScotRec: Social Chain-of-Thought LLM Reasoning for Recommendation
- Modeling Cascaded Delay Feedback for Online Net Conversion Rate Prediction: Benchmark, Insights and Solutions
- Diversity-Augmented Negative Sampling for Implicit Collaborative Filtering
- Delayed Feedback Modeling for Post-Click Gross Merchandise Volume Prediction: Benchmark, Insights and Approaches
- AlphaFree: Recommendation Free from Users, IDs, and GNNs
- Same Last-Item Confusion Unveiled: A Unified Mitigation Framework for Graph Learning in Session-Based Recommendation
- R2NS: Recall and Re-ranking of Negative Samples for Sequential Recommendation
- DynaMoLTV: A Cross-Game Dynamic Mixture Model with Weighted Sub-Distributions for Player Lifetime Value Prediction
- Fusion Is Not A Simple Ensemble! Towards The Evolving Views in Insider Threat Detection
- Diffusion Generative Recommendation with Continuous Tokens
- EEO-TFV: Escape-Explore Optimizer for Web-Scale Time-Series Forecasting and Vision Analysis
- Towards Multi-Label Text Interpretation with Chain-of-Thought Prompting and Contextualized Knowledge
- Evolving Proxy Kills Drift: Data-Efficient Streaming Time Series Anomaly Detection
- Shift-Resilient Diffusive Imputation for Variable Subset Forecasting
- Leveraging LLM and Multiscale Knowledge States to Improve Knowledge Tracing in Programming Tasks
- Re-Diffusion: Modeling Latent Residuals with Diffusion for Time-Series Forecasting
- STPWR: A Spatiotemporal Prediction-based Worker Pre-Recruitment Framework for Mobile Crowd Sensing
- SAGE: Sustainable Agent-Guided Expert-tuning for Culturally Attuned Translation in Low-Resource Southeast Asia
- Genomic-Informed Heterogeneous Graph Learning for Spatiotemporal Avian Influenza Outbreak Forecasting
- LEAP: LLM-Enhanced E-commerce Demand Prediction under Emergent Events
- From Native Memes to Global Moderation: Cross-Cultural Evaluation of Vision–Language Models for Hateful Meme Detection
- Kardia-R1: Unleashing LLMs to Reason toward Understanding and Empathy for Emotional Support via Rubric-as-Judge Reinforcement Learning
- AgriGPT-Omni: A Unified Speech–Vision–Text Framework for Multilingual Agricultural Intelligence
- S²KT:Modeling Uncertainty in Knowledge Tracing via Semantic-aware Structured Gaussian Distributions
- WED-Net: A Weather-Effect Disentanglement Network with Causal Augmentation for Urban Flow Prediction
- Enhancing Content Moderation with LLMs: A Reddit Case Study on Evaluating and Refining Human Decisions
- Mitigating Fine-tuning Bias: A Parameter-Efficient Debiasing Framework for Large Language Models
- AlignCP: Noise-Aware Preference Alignment for LLMs via Confidence and Polarity Reweighting
- Bringing Reasoning to Generative Recommendation Through the Lens of Cascaded Ranking
- AMID: Model-Agnostic Dataset Distillation by Adversarial Mutual Information Minimization
- From Insight to Intervention: Interpretable Neuron Steering for Controlling Popularity Bias in Recommender Systems
- Trireme: A Tripartite Regulation Scheme for Diffusion Models
- BiasEdit: A Training-Free Bias-Detect-and-Edit Framework for Learning Fair Visual Classifiers
- Question the Questions: Auditing Representation in Online Deliberative Processes
- Digital Skin, Digital Bias: Uncovering Tone-Based Biases in LLMs and Emoji Embeddings
- Be Responsible in Your Answers! Monitoring Out-of-Domain Behaviors in Domain-Specific LLMs
- Graph Cross-Domain Continual Fine-Tuning via Orthogonal LoRA Routing with Contrastive Expert Specialization
- Multi-view Hierarchical Graph Contrastive Learning based on Asynchronous Asymmetric Structure
- SPGCL: Subgraph Pattern-Aware Graph Contrastive Learning for High-Order Structural Representation
- Unifying Graph Out-of-Distribution Generalization and Detection through Spectral Contrastive Invariant learning
- CLGNN: A Contrastive Learning-based GNN for Temporal Betweenness Prediction under Extreme Value Imbalance
- Multi-Source Information Driven Spatio-Temporal Hypergraph Learning for Traffic Forecasting
- SGExplainer: Balanced Path-based Signed Graph Neural Network Explanation for Link Sign Prediction
- Dir-GD: Directed Graph Distillation
- STG-DGR: Fraud Detection on Streaming Transaction Graphs with Diffusion-based Generative Replay
- Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance
- PruneRAG: Confidence-Guided Query Decomposition Trees for Efficient Retrieval-Augmented Generation
- Model Editing for New Document Integration in Generative Information Retrieval
- DMAP: Human-Aligned Structural Document Map for Multimodal Document Understanding
- Evidential Matching, Uncertainty Calibration: Towards Robust Composed Video Retrieval with Noisy Triplets
- PairSem: LLM-Guided Pairwise Semantic Matching for Scientific Document Retrieval
- Aligning Multiple Knowledge Graphs in A Single Pass
- CausalSKyHop: Knowledge-Aware Causal Explanation of Dynamic GNNs via Higher-Order Semantic Reasoning
- Conditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion
- How Human Experts Educate Specialized LLMs: Filling Knowledge Gaps in KG-Augmented Generation through Hallucination Detection
- A Unified Framework for Rule Learning: Integrating Commonsense Knowledge from LLMs with Structured Knowledge from Knowledge Graphs
- Cross-city Time Series Forecasting with Retrieval-Augmented Large Language Models
- Glasses: Enabling Fast Environment-aware Few-Shot Learning via Device-Cloud Collaboration
- TimeMar: Multi-Scale Autoregressive Modeling for Unconditional Time Series Generation
- Augmenting Cross-View Geo-Localization with Spatial Semantics from Vision Foundation Models
- SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
- Has the Two-Decade-Old Prophecy Come True? Artificial Bad Intelligence Triggered by Merely a Single-Bit Flip in Large Language Models
- Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework
- ICL-EVADER: Zero-Query Black-Box Evasion Attacks on In-Context Learning and Their Defenses
- Resisting Manipulative Bots in Meme Coin Copy Trading: A Multi-Agent Approach with Chain-of-Thought Reasoning
- The Algorithmic Self-Portrait:Deconstructing Memory in ChatGPT
- Multi-Aspect Mining and Anomaly Detection for Heterogeneous Tensor Streams
- JitterSketch: Finding Jittery Flows in Network Streams
- We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification
- Byte-token Enhanced Language Models for Temporal Point Processes Analysis
- An In-depth Analysis of the Linguistic Characteristics of Science Claims on the Web and their Impact on Fact-checking
- Lifelong Sequential Recommendation with Adaptive Subsequence Compression and Contextual Fusion
- Temporal-Series-Aware Adaptive Positional Encoding for Transformer-based Sequential Recommendation
- BlossomRec: Block-level Fused Sparse Attention Mechanism for Sequential Recommendations
- Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation
- Hyena Operator for Fast Sequential Recommendation
- Guiding Generative Recommender Systems with Structured Human Priors via Multi-head Decoding
- Bridging Explicit and Implicit Intent: Unified Interest Generative Method for Joint Search-Recommendation Modeling
- Field Matters: A Lightweight LLM-enhanced Method for CTR Prediction
- Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce
- GenCI: Generative Modeling of User Interest Shift via Cohort-based Intent Learning for CTR Prediction
- ARCHER: Shooting Straight in Multimodal E-Commerce Search at Alibaba with Progressive Alignment
- Aligning Query Rewriting with Human Cognition and Preference in E-Commerce Search
- TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance
- Thinking Broad, Acting Fast: Latent Reasoning Distillation from Multi-Perspective Chain-of-Thought for E-Commerce Relevance
- From Reasoning LLMs to BERT: A Two-Stage Distillation Framework for Search Relevance
- Concept Relationship Embedding-Based Interactive Web Application for Explainable Medical Diagnosis
- Towards Glaucoma Screening in Decentralized Clinics: A Dynamic Expert-Assisted Domain-Incremental Approach
- XInsight: Integrative Stage-Consistent Psychological Counseling Support Agents for Digital Well-Being
- (Mis-)Informed Consent: Predatory Apps and the Exploitation of Populations with Limited Literacy
- LLM Use for Mental Health: Crowdsourcing Users’ Sentiment-based Perspectives and Values from Social Discussions
- ECLAD: An Edge-Cloud Collaborative Agentic Framework for Interpretable Anomaly Detection in Predictive Maintenance
- PeeriScope: A Multi-Faceted Framework for Evaluating Peer Review Quality
- ARC: A Tool to Rate AI Models for Robustness Through a Causal Lens for Enabling Trustworthy Model Selection
- IntraAI: Bridging Human-AI Understanding Through Intelligent Interface Design
- Sumo x PyPSA: Interactive Web Demo of Real-Time Urban Power-Traffic Co-Simulation with Vehicle-to-Grid
- GreenWebInspector: A Tool for Real-Time Web Energy Efficiency Assessment
- Swen: A Cross‑Platform Desktop Assistant for Instant and Personalized Large‑Language‑Model Interaction
- Click-to-Ask: An AI Live Streaming Assistant with Offline Copywriting and Online Interactive Q&A
- Auditing Textual Context in Sequence-Aware Explainable Recommendation
- MACA: A Multi-Agent Cognitive Adaptation Framework for Human–Agent Collaborative Decision Making
- Rethinking MoE with Retrieval-Memory Synergy: Towards Efficient Expert Coordination
- Exploring Fine-Tuning for Tabular Foundation Models
- MGK-RAG: Multi-Granularity Knowledge Guided Retrieval-Augmented Generation for Radiology Report
- Do You Trust Me? Cognitive–Affective Signatures of Trustworthiness in Large Language Models
- Active Retrieval-Augmented Generation with Conflict-Fused Uncertainty Quantification
- Fact-Checking Strategies in Web: Lateral Navigation in the Browser Boosts Health Misinformation Detection Even Under Confirmation Bias
- Revisiting IPS-based Algorithms for Off-Policy Evaluation of Contextual Bandits
- SAGE-RAI: Design Patterns for Transparent RAG Systems
- Towards Efficient and Interpretable Medical Concept Representation via Ontology-driven Residual Vector Quantization
- Multi-Agent Collaborative Filtering: Orchestrating Users and Items for Agentic Recommendations
- Tuning Qwen2.5-VL to Improve Its Web Interaction Skills
- VK-LSVD: A Large-Scale Industrial Dataset for Short-Video Recommendation
- NERdME: A Named Entity Recognition Dataset for Indexing Research Artifacts in Code Repositories
- Beyond Item-Level Prediction: Fine-Grained CVR Modeling with Price SKU in E-Commerce Recommendation
- Enhancing Trusted Multi-View Classification via Adaptive Regularization Guided by View-Specific Biases
- Orion-Bix: Bi-Axial Attention for Tabular In-Context Learning
- Truth with a Twist: The Rhetoric of Persuasion in Professional vs. Community-Authored Fact-Checks
- Multi-Behavior Sequential Modeling with Transition-Aware Graph Attention Network for E-Commerce Recommendation
- Vertical Semi-Federated Learning for Efficient Online Advertising
- MiniAMIE: Quick and Dirty Rule Mining on Knowledge Graphs
- How Graphs Can Help You Stay Informed in an Evolving World
- What Is Your AI Agent Buying? Evaluation, Biases, Model Dependence, & Emerging Implications of Agentic E-Commerce
- Generalizable Graph-level Anomaly Detection via Prompted Anomaly Expansion and Normality Extraction
- Meta-Learning Driven Few-Shot Knowledge Transfer with Dual-Stage Adaptive Data Replay for Cross-Domain Recommendation
- VecFormer: Towards Efficient and Generalizable Graph Transformer with Graph Token Attention
- Mitigating Homophily Disparity in Graph Anomaly Detection: A Scalable and Adaptive Approach
- Disentangled Graph LLM for Molecule Graph Editing under Distribution Shifts
- KEGOD: Kernel-enhanced Latent Substructure Learning for Graph Out-Of-Distribution Detection
- Hi-GMAE: Hierarchical Graph Masked Autoencoders
- Long-Tailed Recognition of Evidential Experts for Graph-level Classification
- OFA-MAS: One-for-All Multi-Agent System Topology Design based on Mixture-of-Experts Graph Generative Models
- LLM-enhanced Federated Graph Learning with Geometry-aware Graph Projection and Shared Subspace Aggregation
- Rethinking Implicit Hate Speech Detection: Focusing on Latent Hate Components via Dual-Process Argumentation
- PIXEL: Adaptive Steering Via Position-wise Injection with eXact Estimated Levels under a Subspace Calibration
- Doxing-as-a-Service: Demystifying the Chinese Online Doxing Ecosystem
- From Navigation to Intention: Reframing the Web Experience through Goal-Driven Interfaces
- Read as You See: Guiding Unimodal LLMs for Low-Resource Explainable Harmful Meme Detection
- BIND: A Bidirectionally Aligned Next-token Denoising Framework for Fast and Lightweight Deobfuscation of Harmful Web Text
- ToolBox-RL: Learning to Generalize Tool Use Across Massive Repositories
- Facilitating Generative Retrieval with Logical Denoising for Interpretable Conversational Search
- Beyond More Context: Retrieval Diversity Boosts Multi-Turn Intent Understanding
- PaperAsk: A Benchmark for Reliability Evaluation of LLMs in Paper Search and Reading
- SeaRAG: Reducing Hallucination in Retrieval-Augmented Generation via Statement-Entity Adaptive Ranking
- Experience is the Best Teacher: Augmenting LLM Reasoning with Knowledge Learned from the Past
- Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learning
- Verifiable Federated Representation Learning for Cross-domain Sequential Recommendation
- Kleene Closure Property Path Query Optimization Based on Node Clustered Index
- AgentPRM: Process Reward Models for LLM Agents via Step-Wise Promise and Progress
- A Simplex Approach to Synthetic Knowledge Graph Generation
- Detecting Miscitation on the Scholarly Web through LLM-Augmented Text-Rich Graph Learning
- Empowering LLMs for Structure-Based Drug Design via Exploration-Augmented Latent Inference
- A Unified and Time-Efficient Multi-Agent Framework for Data Discovery
- SentinelNet: Safeguarding Multi-Agent Collaboration Through Credit-Based Dynamic Threat Detection
- Anti-Phishing Training (Still) Does Not Work: A Reproduction of Phishing Training Inefficacy Grounded in the NIST Phish Scale
- Real or Rogue? Detecting Malicious Miniapps with Deceptive Reporting Interface
- Reliable Non-Leveled Homomorphic Encryption for Web Services
- Acting Flatterers via LLMs Sycophancy: Combating Clickbait with LLMs Opposing-Stance Reasoning
- DeepSVU: Towards In-depth Security-oriented Video Understanding via Unified Physical-world Regularized MoE
- SPCA: Stream Parser Confusion Attack for Web Application Firewall Evasion in HTTP/2
- SemFuzz: A Semantics-Aware Fuzzing Framework for Network Protocol Implementations
- DRGW: Learning Disentangled Representations for Robust Graph Watermarking
- PrivSniffer: Graph-based Contextual Privacy Leakage Detection for User-Generated Texts
- Can Multimodal LLMs Perform Time Series Anomaly Detection?
- MF^3: Multimodal Federated Learning with Dual-Path Mamba-Transformer for Metro Flow Prediction
- An LLM-Powered Cooperative Framework for Large-Scale Multi-Vehicle Navigation
- Alzo: Auto-Tuning with Reinforcement Learning for DAG-based Blockchains
- Concordia: Enabling Low-Conflict Distributed Transaction Scheduling in Sharding Blockchain via Cooperative Perception
- SecureSplit: Mitigating Backdoor Attacks in Split Learning
- Predictability-Aware Compression and Decompression Framework for Multichannel Time Series Data with Latent Seasonality
- From Criteria to Ranking: Targeting-Aware Tripartite Graph Learning for Multi-Criteria Recommendation
- SAGE: Global Semantic Alignment with LLMs for Long-Tail Sequential Recommendation
- Relation-aware Diffusion-Asymmetric Graph Contrastive Learning for Recommendation
- Adaptive Location Hierarchy Learning for Long-Tailed Mobility Prediction
- Scaling Collaborative Filtering with Multimodal Contrastive Fine-tuning
- Embedding Enhancement via Fine-Tuned Language Models for Learner-Item Cognitive Modeling
- Spattack: Subgroup Poisoning Attacks on Federated Recommender Systems
- Quantifying User Coherence: A Unified Framework for Analyzing Recommender Systems Across Domains
- ONeRec: Towards Openness-Aware and Adaptive Proactive News Recommendation
- Sharpness-Consistent Cross-Domain Recommendation for Cold-Start Items
- Sharpness-Aware Minimization for Generalized Embedding Learning in Federated Recommendation
- Dynamic Experts Synergy for Multi-Task Recommendation
- Mitigating Cognitive Vulnerabilities in Code Generation via Multi-Agent Adversarial Debate
- E2PL: Effective and Efficient Prompt Learning for Incomplete Multi-view Multi-Label Class Incremental Learning
- CIDC: Cluster Identification-Guided Dual Correction for Robust Short Text Clustering
- Mamba Hawkes Process for Event Sequence Modeling
- StreamFP: Fingerprint-guided Data Selection for Efficient Stream Learning
- Interpretable Dynamic Network Modeling of Tensor Time Series via Kronecker Time-Varying Graphical Lasso
- Bias Mitigation for Harmful Meme Detection using Front-door Adjustment
- VL-KGE: Vision–Language Models Meet Knowledge Graph Embeddings
- GRank: Towards Target-Aware and Streamlined Industrial Retrieval with a Generate-Rank Framework
- Delay-Aware Graph Neural Stochastic Differential Equations for Financial Time Series Modeling and Forecasting
- AFE-Master: Enhancing LLM-Driven Autonomous Feature Engineering with Domain-Specific Language Parsing and Guided Local Search
- StreamSense: Streaming Social Task Detection with Selective Vision–Language Model Routing
- FairFRL: Fairness-aware Federated Representation Learning for Cross-domain Sequential Recommendation
- CEAT: Context-Emotion Adversarial Training Framework for Robust Emotion-Driven Fraud Detection
- HCSL: Rumor Detection by Integrating Intra-Sample Curriculum Learning and Hierarchical Semantic Learning
- Physics-Aware Multimodal Urban Heat Mapping with Open Web Imagery and Mobility Data
- Safeguarding Children at Scale: Cost-Effective Multimodal LLM Detection of Inappropriate YouTube Advertising
- Credit and Power Co-evolution Modeling with Dynamic Graph Learning
- Mind the Ambiguity: Aleatoric Uncertainty Quantification in LLMs for Safe Medical Question Answering
- SMART: A Social Movement Analysis & Reasoning Tool with Case Studies on #MeToo and #BlackLivesMatter
- FUSED: Toward Federated Multimodal Retrieval across Sovereign Data Domains
- Cross-Domain Fake News Detection on Unseen Domains via LLM-Based Domain-Aware User Modeling
- COMA: A Collaborative Multi-Role Agent Framework for Automated Lesson Plan Generation
- From Words to Worlds: Measuring Cultural Narrative Bias in LLMs via a Structural–Value Pipeline
- CompTox Ontology: Leveraging Knowledge Graphs for PFAS Monitoring and Decision-Making
- RegimeGuard: Continual Learning Queue Scheduling for Socially Critical Web Services
Friday, July 3, 2026
- Does This Button Work? Investigating YouTube's Ineffective User Controls
- Users Pay Twice: The Hidden Energy Cost of Web Advertising
- Towards LLM-centric Affective Visual Customization via Efficient and Precise Emotion Manipulating
- D-Models and E-Models: Diversity-Stability Trade-offs in the Sampling Behavior of Large Language Models
- Dynamics of Human-AI Collective Knowledge on the Web: A Scalable Model and Insights for Sustainable Growth
- Hierarchical Graph-Bag-Network for Self-Supervised Multi-Graph Learning
- From Representation to Clusters: A Contrastive Learning Approach for Attributed Hypergraph Clustering
- AC$^2$L-GAD: Active Counterfactual Contrastive Learning for Graph Anomaly Detection
- A Dual-Channel Contrastive Learning Framework for Anomaly Detection in Dynamic Graph Structures
- Structure-Semantic Synergized Deep Contrastive Graph Clustering
- Multimodal Graph Conditioned Diffusion Model for Video Captioning
- MMTableBench: A Multi-level Multimodal Benchmark for Reasoning and Layout Complexity in Table QA
- Adaptive Task Balancing for Visual Instruction Tuning via Inter-Task Contribution and Intra-Task Difficulty
- Multimodal Trajectory Representation Learning for Travel Time Estimation
- Towards Foundation Models for MMKG: Multi-Task Inductive Generalization via Task-Aware Routing
- LoVR: A Benchmark for Long Video Retrieval in Multimodal Contexts
- LongRanker: Efficient One-Pass Document Reranking with Long-Context Large Language Models
- Breaking the Single-Reference-Vector Barrier in Approximate Nearest Neighbor Search
- OpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAG
- DocResearcher: A Unified System for Multimodal Document Parsing and Deep Research
- Dual History Enhancement with Hybrid Hypergraph-Graph Networks for Temporal Knowledge Graph Reasoning
- STARK: Structure-Aware and Adaptive Representation Learning for Continual Knowledge Graph Embedding
- Unlearning of Knowledge Graph Embedding via Preference Optimization
- Conditional Information Extraction with Diffusion Model on Fact-Condition Star Graph
- Learning to Evolve: Bayesian-Guided Continual Knowledge Graph Embedding
- Eclipse Attacks on Ethereum’s Peer-to-Peer Network
- Proteus: Towards Accurate and Low-overhead In-Network Malicious Traffic Detection
- Tracking the Stray Sheep: Understanding DNS Response Manipulation in the Wild
- Sybil Attacks on Centrality Measures
- GIANT: Structure-Agnostic Practical Adversarial Attacks for Graph-based Network Intrusion Detection Systems
- Investigating Web Content Delivery Performance over Starlink
- Breath: Adaptive Protection Boundary in FEC Encoding for Mobile Real-Time Video Streaming
- Camel: Frame-Level Bandwidth Estimation for Low-Latency Live Streaming under Video Bitrate Undershooting
- DualDis: A Dual Disentanglement Network for Vehicle Re-identification
- FediScan: Collaborative Social Bot Detection in the Fediverse
- WAMO: Toward Secure Browser Inference via Web Model Obfuscation in WebAssembly
- WebGeoInfer: Structure-Free Multi-Stage Framework for Geolocation Inference from Exposed Device Web Interfaces
- FalconScope: Effective and Efficient Detection of Hidden Web Interfaces in IoT Devices
- Bento: Fine-Grained Memory Isolation for COTS WebAssembly Binaries
- Risk-free Selfish Mining in Hybrid Predictability Model. A Case Study on Polkadot’s NPoS
- Anchor Drift No More: Hierarchical Consistency-Guided Prompt Distillation for Incomplete Multimodal Learning
- LoRA-E^2: Effective and Efficient Low-rank Adaptation
- Reinforcement Learning with Verbalized Probabilities for LLM Classification
- Multistage Feedback-Driven Causal Discovery from Textual Data with Large Language Models
- Inference Cost Attacks for Retrieval-Augmented Large Language Models
- ES-MemEval: Benchmarking Conversational Agents on Personalized Long-Term Emotional Support
- Learning Evolving Preferences: A Federated Continual Framework for User-Centric Recommendation
- Prototype-Aligned Federated Soft-Prompts for Continual Web Personalization
- Modeling Stage-wise Evolution of User Interests for News Recommendation
- MemWeaver: A Hierarchical Memory from Textual Interactive Behaviors for Personalized Generation
- Personalized Parameter-Efficient Fine-Tuning of Foundation Models for Multimodal Recommendation
- MCRec: Few-Shot Multimodal Cover Recommendation via User Interest Profiles
- Drifting with Intent: Generative Interest Trajectories for Multimodal Web Recommendation
- TargetMR: Learning Modality Target for Multimodal Recommendation
- Multimodal-enhanced Federated Recommendation: A Group-wise Fusion Approach
- A Long-term Value Prediction Framework In Video Ranking
- GAM: A Generative Auto-Marketing Framework in Online E-commerce Platforms
- Make It Long, Keep It Fast: End-to-End 10k-Sequence Modeling at Billion Scale on Douyin
- When Rules Fall Short: Agent-Driven Discovery of Emerging Content Issues in Short Video Platforms
- Visual Content Moderation in Messaging Systems
- Fairer AI Carbon Accounting: Incorporating Market-based Attribution and Uncertainty in Embodied and Operational Carbon Footprint
- EcoThink: A Green Adaptive Inference Framework for Sustainable and Accessible Agents
- GreenTune: Energy-Efficient Low-Rank Tuning of LLMs with ThreeE Evaluation under 4-/8-bit Quantization
- Route-and-Reason: Energy-Efficient Scaling of LLM Reasoning via Reinforced Model Routing
- Online GPU Energy Optimization with Switching-Aware Bandits
- QueryGym: A Toolkit for Reproducible LLM-Based Query Reformulation
- MetriKG: Profiling Static and Evolving Knowledge Graphs
- TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models
- RobustReviewAI: A Robustness Evaluation System for AI-Powered Peer Review
- LLM-Powered Structurer: Normalizing Natural Language to Information Delivery Specification for Industrial Data Exchange
- OwlerLite: Scope- and Freshness-Aware Web Retrieval for LLM Assistants
- Weakly Supervised Multimodal Claim Verification with Entity-Graph Inference
- BLURR: A Boosted Low-Resource Inference for Vision-Language-Action Model
- Linguistic Signatures for Enhanced Emotion Detection
- PRISM: LLM-Guided Semantic Clustering for High-Precision Topics
- CitiLink-Summ: A Dataset of Discussion Subjects Summaries in European Portuguese Municipal Meeting Minutes
- Multi-Modal Enhanced Graph Transfer Learning for Digital Finance Fraud Detection
- Designing for the Next Click: Bandits for Real-Time Page Layout
- Deepfakes in the 2025 Canadian Election: Prevalence, Partisanship, and Platform Dynamics
- Edit-Level Tracking of Narrative Changes in 10-K Filings
- Real-Time Trend Prediction via Continually-Aligned LLM Query Generation
- Uncertainty-Aware Web-Conditioned Scientific Fact-Checking
- Towards Token-Level Text Anomaly Detection
- llm-tuna - Hyperparameter Optimization for LLM Inference
- From Random Forget-Sets to Realistic Natural-Language Deletion Requests
- Retrieval Collapses When AI Pollutes the Web
- Multimodal Topic Discovery in Web Media via von Mises-Fisher Mixture Neural Topic Models
- Predicting Expectancy Violations Using Eye-Tracking Features: A Machine Learning Approach
- SEER: Set Encoding for Efficient Representation in Large-Scale E-commerce
- ReSuMe: Retriever-Summarizer Mutual Enhancement via Reinforcement Learning
- Agent-Enhanced Heterogeneous Graph RAG for Academic Question Answering
- Causal Pre-training Under the Fairness Lens: An Empirical Study of TabPFN
- STAR: Semantic Table Representation with Header-Aware Clustering and Adaptive Weighted Fusion
- ULoR: Uncertainty-Aware Leave-One-Out Refinement Framework for Diagnosis Prediction
- Lurkers, Interactors, Creators: Modeling Behavioral and Ideological Diversity on X
- Tabular Foundation Models are Strong Graph Anomaly Detectors
- Weighted Reservoir Sampling with Replacement from Data Streams
- Multi-field Balance-aware Calibration of Predictions in Online Advertising
- SLFM: Semi-Supervised Local Community Detection Based on Hyperbolic Flow Matching
- Contextual Structure-Enhanced Selective Graph Convolutional Network
- WPIS: From In-the-Wild Web Images to Physics-Aware 3D Scene Graphs for Physical Reasoning
- Revisiting and Enhancing Graph Neural Networks through the Lens of Amortized Flows
- STELA: Spatiotemporal Forecasting via Graph Learning and Entropy-Guided LLM Adaptation
- Towards Geometry-Consistent Federated Graph Learning
- Stuart-Landau Oscillatory Graph Neural Network
- Rethinking Graph Generalization through the Lens of Sharpness-Aware Minimization
- RARD: Rationale-First Blockwise Autoregressive Diffusion in Rationale‑Dominated Graph Generation
- Space-based Parameter Evolving with Lightweight Optimization for Graph Adaptation to Evolving Shifts
- Robust Fake News Detection using Large Language Models under Adversarial Sentiment Attacks
- MultiFPT: Towards Multi-Attribute Fairness in Pre-Trained Graph Neural Networks via Prompt Tuning
- Is Contextual Advertising Safe? Analyzing Systemic Risks with Ads on YouTube
- Unifying Diversity and Fairness in Re-ranking via Economic Growth Theory
- Emergence of Structural Disparities in the Web of Scientific Citations
- IO-X: Detecting and Attributing Content-Duplicating Influence Operations on X (Twitter)
- Characterizing Iran's Phased National Internet Shutdown in 2025: A Progressive and Distributed Action
- Rethinking Soft Compression in Retrieval-Augmented Generation: A Query-Conditioned Selector Perspective
- SketchMind: Understanding Abstract Sketches with MLLMs for Fine-Grained Sketch-Based Image Retrieval
- A Unified Framework for Context-Aware and Relation-Aware Graph Retrieval-Augmented Generation
- AgenticShop: Benchmarking Agentic Product Curation for Personalized Web Shopping
- CFVBench: A Comprehensive Video Benchmark for Fine-grained Multimodal Retrieval-Augmented Generation
- TRACE: Trajectory-Aware Comprehensive Evaluation for Deep Research Agents
- Expectation-Guided Self-Verification for Aligning Large Reasoning Models with Domain Knowledge
- Incentivizing Agentic Reasoning Capability with Outcome Supervision for Knowledge Base Question Answering
- Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation
- MixRAG : Mixture-of-Experts Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
- AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation
- Dual-View Hypercube Alignment Framework for Open-World Entity Typing
- Counterfactual Meta-task Augmentation for Few-shot Graph Node Classification
- Knowledge-Enhanced Multimodal Fake News Detection: Semantic Visual and Priority Fusion
- BLEND: Balanced and Leaf-Enhanced Dual Fine-Tuning for Taxonomy Completion
- Does Ad-Free Mean Less Data Collection? An Empirical Study of Platform Data Practices and User Expectations
- Balancing Privacy and Security of QNAME Minimisation
- Do You Really Know What I Am Doing? Backdoor Attacks on Provenance-Based Intrusion Detection Systems
- Trust on Reload: Securing Browser-Based End-to-End Encryption
- Fast or Secure? Push the Limit of Privacy Leakage Threat via Charging Side-Channel Attacks
- PeriNet: Periodic Deep Learning Framework for Modality-Agnostic Privacy Preserving
- CogAgent: Self-Evolving Cognitive Agents for Multi-Source Fraud Detection in Heterogeneous Financial Networks
- Evasion Under Blockchain Sanctions
- Unveiling the Underground Phishing Ecosystem: A 12-Year Longitudinal Study of Deep and Dark Web Forums
- YouChoose: A Lightweight Anonymous Proof of Account Ownership
- Fate: Fast Edge Inference of Mixture-of-Experts Models via Cross-Layer Gate
- BIND: Enabling Continuous Transaction Processing During Account Migration in Sharded Blockchains
- Adaptive Model and Strategy Routing for Cost-Efficient LLM Services
- MetaKube: An Experience-Aware LLM Framework for Kubernetes Failure Diagnosis
- Amortized Predictability-aware Training Framework for Time Series Forecasting and Classification
- FovRL: Joint Foveation and Quality Control for Immersive VR Streaming Using Reinforcement Learning
- SuperEar: Eavesdropping on Mobile Voice Calls via Stealthy Acoustic Metamaterials
- FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Clients
- Talos: Optimizing Top-K Accuracy in Recommender Systems
- From Token to Item: Enhancing Large Language Models for Recommendation via Item-aware Attention Mechanism
- Following the TRAIL: Predicting and Explaining Tomorrow’s Hits with a Fine-Tuned LLM
- QDDR: Quality-Driven Intent Disentanglement with Dual-Path Modeling for Recommendation
- IMPerSumm: Information-Modulated User Preference Modeling for Personalized Text Summarization
- CCL-Diff: Representation-Consistent Diffusion with Intrinsic Contrastive Learning for Recommender Systems
- Exploration Sizing via Model-Predictive Control
- Post-hoc Popularity Bias Correction in GNN-based Collaborative Filtering
- Identifying and Upweighting Power-Niche Users to Mitigate Popularity Bias in Recommendations
- Efficient Content-based Recommendation Model Training via Noise-aware Coreset Selection
- DrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agents
- TopKGAT: A Top-K Objective-Driven Architecture for Recommendation
- Taming the Long Tail: Efficient Item-wise Sharpness-Aware Minimization for LLM-based Recommender Systems
- GlassMiner: Mining Looking Glass Services via Structure-Semantics Fusion for Web Observability
- From Newborn to Impact: Bias-Aware Citation Prediction
- FedRMamba: Federated Residual Mamba for Multivariate Time-Series Forecasting
- Prompt-Induced Linguistic Fingerprints for LLM-Generated Fake News Detection
- BARouter: A Budget-adaptive Online Large Language Model Router Framework
- Moral Outrage Shapes Commitments Beyond Attention: Multimodal Moral Emotions on YouTube in Korea and the US
- Dynamic Multi-period Experts for Online Time Series Forecasting
- Unlocking the Multilingual Long-Tail Web: A Fused Macro-Micro Framework for Scalable Content Analysis
- Bridging Cognitive Neuroscience and Graph Intelligence: Hippocampus-Inspired Multi-View Hypergraph Learning for Web Finance Fraud
- Energy-Efficient Training-Free Zero-Inflation Correction for Rainfall Forecasting with Time-Series Foundation Models
- HAAF: Hierarchical Adaptation and Alignment of Foundation Models for Few-Shot Pathology Anomaly Detection
- Language-Guided Game-Theoretic Fairness in Web-Enabled Energy Networks
- Audit‑of‑Audits for the Web: Bayesian Meta‑Evaluation that Yields Interval‑Valued, Threshold‑Aligned Fairness Claims
- VC-Soup: Value-Consistency Guided Multi-Value Alignment for Large Language Models
- Communication-Efficient Federated Learning for Post-Flood Risk Assessment using UAV Swarms
- DAPWeb: Construct-Aligned Evaluation of MLLMs for Web-Based Child Mental Screening
- Multimodal Spatiotemporal Forecasting of Deepfake Propagation on Social Media
- K&L: Penetrating Backdoor Defense with Key and Locks
- EmeraldMind: A Knowledge Graph–Augmented Framework for Greenwashing Detection
- Understanding the Consequences of VTuber Reincarnation
- Intelli-Planner: Towards Customized Urban Planning via Large Language Model Empowered Reinforcement Learning
- Cross-Modal Rationale Transfer for Explainable Humanitarian Classification on Social Media
- The Power of Penalties: Negativity-Aware Incentives for High-Quality Crowdsourced Data Labeling
- From Retrieval to Generation: Unifying External and Parametric Knowledge for Medical Question Answering
- When to Trust: A Causality-Aware Calibration Framework for Accurate Knowledge Graph Retrieval-Augmented Generation
- Multi-Source Unsupervised Graph Domain Adaptation via Concise Propagation–Transformation Pipeline
- Graph Neural Network Model Transferability Estimation via Decomposition-Augmented Discriminant Analysis
- PIGCN: Physics-Inspired Graph Convolution Networks for Heterogeneous Social Event Detection
- MessageShift: Fine-Grained Data Augmentation for Graph Neural Networks
- Collaborative Subgraph Learning based Spectrum Sensing under Partial Observations
- ReaLM: Residual Quantization Bridges Knowledge Graph Embeddings and Large Language Models
- Language Model Representations for Efficient Few-Shot Tabular Classification
- KG-BiLM: Knowledge Graph Embedding via Bidirectional Language Models
- TaxoBell: Gaussian Box Embeddings for Self-Supervised Taxonomy Expansion
- Node Role-Guided LLMs for Dynamic Graph Clustering
- MCoT-MVS: Multi-level Vision Selection by Multi-modal Chain-of-Thought Reasoning for Composed Image Retrieval
- BANCO: Drift-Aware Batched Bandits for Adaptive Proximity Graph Pruning
- Enhancing Domain-Adaptive Hashing via Evidential Learning and Progressive Alignment
- Diversifying Differentiable Graph Retrieval with Topic-Adaptive Multi-Intent Learning
- Cost-Aware Retrieval-Augmentation Reasoning Models with Adaptive Retrieval Depth
- DSTAG: A Semantic Tag-Enhanced Dual-Graph Convolutional Network for Temporal Knowledge Graph Completion
- Plan Then Retrieve: Reinforcement Learning-Guided Complex Reasoning over Knowledge Graphs
- MemoTime: Memory-Augmented Temporal Knowledge Graph Enhanced Large Language Model Reasoning
- PRoH: Dynamic Planning and Reasoning over Knowledge Hypergraphs for Retrieval-Augmented Generation
- Beyond Single Pass, Looping Through Time: KG-IRAG with Iterative Knowledge Retrieval
- SaGD: A Node-Level Differentially Private Graph Learning Framework with Sensitivity-Aware Gradient Descent
- Mitigating Cumulative Privacy Risk in Continual Information Sharing: A Dynamic Stackelberg Game Approach
- Distribution-Aligned Synthetic Text Generation via Tail-Aware Enhancement
- Inferring Users’ Demographics and Sensitive Interests Using the Topics API
- AdVersa: Adversarially-Robust and Practical Ad and Tracker Blocking in the Wild
- Beyond Single view Decoding: Dual-view Map Inference from Trajectories via Primal-Dual Graphs Co-generation
- ST-LEGO: Large Language Models as Modular Architects for Traffic Prediction
- HALO: Hierarchical Reinforcement Learning for Large-Scale Adaptive Traffic Signal Control
- AgentSense: LLMs Empower Generalizable and Explainable Web-Based Participatory Urban Sensing
- TRACE: Trajectory Recovery with State Propagation Diffusion for Urban Mobility
- Exploring and Exploiting Security Vulnerabilities in Self-Hosted LLM Services
- PADD: Prefix-based Attention Divergence Detector for LLM Jailbreaks
- The Asymmetric Vulnerability: Bypassing LLM Defenses via Guardrail-Model Mismatch
- Greedy Attack: Breaking Finality against VeChain Proof-of-Authority Consensus Protocol
- JANUS: A Dual-Constraint Generative Framework for Stealthy Node Injection Attacks
- Beyond Patches: Superpixel Token-based Transformers for Attribute-Specific Fashion Retrieval
- VarParser: Unleashing the Neglected Power of Variables for LLM-based Log Parsing
- ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks
- VisionST: Coordinating Cross-modal Traffic Prediction with Interactive Geo-image Encoding
- UrbanMoE: A Sparse Multi-Modal Mixture-of-Experts Framework for Multi-Task Urban Region Profiling
- SEAR: LLM-Powered Sequential Recommendation via Fusion of Collaborative, Semantic, and Rating Information
- Retracing and Restoring: Chronological Context Preservation for Effective Dynamic Recommendation
- FCRLLM: Aligning LLM with Collaborative Filtering for Long-tailed Sequential Recommendation
- Generative Archetype-Grounded Item Representations for Sequential Recommendation
- Token-level Collaborative Alignment for LLM-based Generative Recommendation
- Pathways of Thoughts: Multi-Directional Thinking for Long-form Personalized Question Answering
- HyMiRec: A Hybrid Multi-interest Learning Framework for LLM-based Sequential Recommendation
- Dynamic Routing-Based Adaptive Multi-LLM Collaboration: A Unified Recommendation Framework with Decision Knowledge Complementation
- AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents
- Does LLM Focus on the Right Words? Mitigating Context Bias in LLM-based Recommenders
- Multi-Domain Marker Aggregation for Threat Detection in Cloud Environments
- Smart Eye: LLM-Guided Proposer-Verifier Framework for Industrial-Scale Log Anomaly Detection
- URLBank: Data-Driven URL Discovery via Temporal Link Graphs
- Orchestration-Free Customer Service Automation: A Privacy-Preserving and Flowchart-Guided Framework
- Multilingual Reference Need Assessment System for Wikipedia
- Belief-Driven Multi-Agent Collaboration via Approximate Perfect Bayesian Equilibrium for Social Simulation
- Think Then Recommend: An LLM-Powered Multi-Agent Framework for Personalized Conversational Recommender System in E-Commerce
- GORAG: Graph-based Online Retrieval Augmented Generation for Dynamic Few-shot Social Media Text Classification
- Mining Citywide Dengue Spread Patterns in Singapore Through Hotspot Dynamics from Open Web Data
- Consensus Stability of Community Notes on X
- Semi-Supervised Fake News Detection with Mixture of Experts
- IConMoE: Modeling Intents of Misinformation using Concept Activation Vector-based Mixture of Experts
- Causality Guided Representation Learning for Cross-Style Hate Speech Detection
- Navigating Truth in Multimodal Fact-checking via Retrieval- and Reasoning-Enhanced Large Language Models
- It's not Easy: Applying Supervised Machine Learning to Detect Malicious Extensions in the Chrome Web Store