Accepted Workshops
Important Dates
- Paper submission:Mid December - Early January (please check the workshop websites for specific deadlines)
- Paper notification:January 13, 2026
- Camera ready: February 2, 2026
All submission deadlines are end-of-day in Anywhere on Earth (AoE) time zone.
Description: TBD
Organizers: Marc Spaniol (University of Caen Normandy Caen), France Omar Alonso (Amazon Santa Clara, CA, USA), Ricardo Baeza-Yates (KTH, Royal Institute of Technology Stockholm, Sweden)
Website: https://temporalweb.net/
Description: The rise of foundation models (FMs) amplifies the importance and relevance of federated learning (FL) as a crucial research direction. With FMs becoming the norm in machine learning development, the focus shifts from model architecture design to tackling the issues surrounding privacy-preserving and distributed learning. Advancements in FL methods have the potential to unlock the use of FMs, enabling efficient and scalable training while safeguarding sensitive data. With this in mind, we invite original research contributions, position papers, and work-in-progress reports on various aspects of federated learning in the era of foundation models. Since the emergence of foundation models has been a relatively recent phenomenon, their full impact on federated learning has not yet been well explored or understood. We hope to provide a platform to facilitate interaction among students, scholars, and industry professionals from around the world to discuss the latest advancements, share insights, and identify future directions in this exciting field.
Organizers: 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), Liping Yi (Tianjin University)
Description: TBD
Organizers: Dr. Lei Wang (Griffith University & Data61/CSIRO), Dr. Md Zakir Hossain (Curtin University), Prof. Tom Gedeon (Curtin University), Dr. Syed Mohammed Shamsul Islam (ECU), Prof. Rafiqul Islam (Charles Sturt University), Dr. Yasmeen George (Monash University), Dr. Shreya Ghosh (The University of Queensland)
Description: The emerging Web era of Intelligence (AI) presents a paradox: the same innovations that threaten security and truth also offer unprecedented solutions. AI technologies are becoming ever more interwoven in the fabric of online systems, presenting potential that can be used both for constructive and destructive purposes. In the post-truth era, generating persuasive yet deceptive content and automating social engineering attacks and the spread of disinformation has never been easier since the conception of the World Wide Web. At the same time, there exist exceptional opportunities for innovation and creating powerful tools to mitigate these threats, thanks to intrusion detection, threat modeling, and context-aware access control, etc. The AiOfAi workshop, which has had three prior editions at the International Joint Conference on Artificial Intelligence (IJCAI), aims to highlight 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. We will discuss the societal impact of widespread adoption of AI tools, especially with the advent of Generative AI and its consequences, ranging from the erosion of public trust to the blurring privacy lines. AiOfAi will also address the ethical and legal frameworks needed to guide responsible AI deployment, which embodies fairness, transparent decision-making, and privacy preservation. We aim to bring together researchers, practitioners, and enthusiasts interested in AI, cybersecurity, ethics, law, and human computer interaction to discuss methodologies, case studies, and tools that address the complex tradeoffs between AI capabilities and vulnerabilities. We welcome original contributions that present innovative ideas, proof of concepts, and use cases to tackle the challenges of the AI-powered Web.
Organizers: Esma Aïmeur (Université de Montréal), Rim Ben Salem (Polytechnique Montréal), Dorsaf Sallami (Université de Montréal), Julita Vassileva (University of Saskatchewan), Nora Boulahia-Cuppens (Polytechnique Montréal)
Description: TBD
Organizers: Stefan Dietze (Heinrich-Heine-University Düsseldorf & GESIS, Germany), stefan.dietze[[AT]]gesis.org, Dimitar Dimitrov (GESIS, Germany), dimitar.dimitrov[[AT]]gesis.org, Pavlos Fafalios (Technical University of Crete & FORTH-ICS, Greece), pfafalios[[AT]]tuc.gr, Konstantin Todorov (University of Montpellier / LIRMM / CNRS, France), todorov[[AT]]lirmm.fr
Description: TBD
Organizers: Rima Dessi' (Higher College of Technologies, United Arab Emirates), Jeenu Joy (FIZ-Karlsruhe, Germany), Danilo Dessi' (University of Sharjah, United Arab Emirates), Francesco Osborne (Knowledge Media Institute, The Open University, United Kingdom), Hidir Aras (FIZ-Karlsruhe, Germany)
Website: https://semtech4stld.github.io/
Description: The Agentic Web is emerging as billions of AI agents discover, communicate, and coordinate across the open Web, marking a shift toward systems that no longer operate as isolated models but as Web-integrated entities. This workshop unifies architectures and standards with the foundations of interoperable ecosystems, convening researchers and practitioners to chart a shared agenda. We focus on web-native building blocks: agent registries and resolution, identity and credentials (DIDs/VCs), authorization (OAuth 2.0), discovery (DNS-SD), and federation patterns (e.g., ActivityPub), and their interfaces with application-level protocols (A2A, MCP, OpenAPI/REST/GraphQL/gRPC) and corresponding architectural models. Beyond wiring, we examine economic mechanisms (reputation under adversarial conditions, knowledge pricing, transaction protocols) and societal coordination (governance, accountability, evaluation at population scale). Topics include capability representation and matching, cross-protocol bridges, privacy and provenance, workflow orchestration, and reliable tool use over heterogeneous data and services spanning cloud, edge/IoT, and enterprise environments, as well as emerging patterns that let AI systems operate across distributed Web environments. These directions align with the emerging need to support function calling, tool use, and multi-agent coordination over heterogeneous Web resources, leveraging open and lightweight protocols to interact securely with distributed data and services. The program blends keynote, invited talks, papers, and a panel to surface design principles, pitfalls, and testbed practices. By aligning standards, infrastructure, and incentives, the workshop seeks to ensure the Agentic Web remains open, trustworthy, and sustainable.
Organizers: Abderrahmane Maaradji (University of Doha for Science and Technology, Qatar), Abul Ehtesham (Kent State University, USA), Aditi Singh (Cleveland State University, USA), Boualem Benatallah (Dublin City University, Ireland), Fatma Outay (Zayed University, UAE), Luca Muscariello (Cisco Systems, France), Pradyumna Chari (MIT Media Lab, USA), Ramesh Raskar (MIT Media Lab, USA), Sabrina Senatore (University of Salerno, Italy), Yacine Sam (University of Tours, France)
Website: https://faaw.univ-tours.fr/
Description: TBD
Organizers: Thomas Mandl (University of Hildesheim, Germany), Haiming Liu (University of Southampton, UK), Gautam Kishore Shahi (University of Duisburg-Essen, Germany), Amit Kumar Jaiswal (Indian Institute of Technology (BHU) Varanasi, India), Durgesh Nandini (University of Bayreuth, Germany), Luis-Daniel Ibáñez (University of Southampton, UK), Dr. Junichi Suga (Fujitsu Research Japan), Dr. Dai Yamamoto (Fujitsu Research Japan), Dr. Rahul Mishra (Fujitsu Research India), Dr. Rajakrishnan P. Rajkumar (IIIT Hyderabad, India), Dr. Sagar Uprety (University College London (UCL), UK), Dr. Sujit Kumar (Nanyang Technological University (NTU), Singapore), Dr. Bornali Phukon (University of Illinois Urbana-Champaign (UIUC), USA)
Description: TBD
Organizers: Keerthi Gopalakrishnan (Walmart Global Tech, USA), Qi Xu (Meta AI, USA), Aysenur Inan (Walmart Global Tech, USA), Zhigang Hua (Meta AI, USA), Shuang Yang (Meta AI, USA), Luyi Ma (Walmart Global Tech, USA)
Description: ZABAPAD (Zero-knowledge proof And Blockchain for WEB 4.0: Advancing the Post-quantum And Decentralized Era) is a workshop focusing on zero-knowledge technologies, blockchain infrastructure, and post-quantum readiness for the emerging Web 4.0 ecosystem. This half-day, single-track event emphasizes real-world deployments, empirical measurements, and interoperability across Web and non-Web domains. In particular, ZABAPAD explores the convergence of AIoT and ZKP—redefining identity and trust models beyond SIM in mobile networks, IP in Web 2.0, and NFT in Web 3.0. As AIoT systems evolve toward decentralized, post-quantum infrastructures, ZKP-based authentication and AIoT SIM functionalities are emerging as key enablers of secure, privacy-preserving, and verifiable connectivity among intelligent devices, vehicles, and edge services. This theme extends to ZKML, Layer-2 proving/verification, TEE+ZK integration for verifiable compute, and post-quantum migration of identities, wallets, ledgers, and protocols. Expected outcomes include: (1) a practitioner-oriented adoption playbook, (2) an interoperability and standards checklist, (3) a curated set of reproducible benchmarks and datasets, and (4) a catalog of failure modes and mitigations for domains such as finance, mobility, healthcare, AIoT, public services, supply chain, and AI/ML. ZABAPAD complements the Web Conference and Web 4.0 communities by uniting global researchers and developers to chart actionable, trustworthy pathways toward the post-quantum, decentralized, and intelligent Internet.
Organizers: Shiho Kim (Yonsei University, South Korea), Ho Suk (Yonsei University, South Korea), Roberto Di Pietro (King Abdullah University of Science and Technology, Saudi Arabia), Davor Svetinovic (Khalifa University, United Arab Emirates), KyungHi Chang (Inha University, South Korea), Madhusudan Singh (Pennsylvania State University, USA), Rakesh Shrestha (Research Institutes of Sweden, Sweden)
Website: https://zabapad.github.io
Description: This is the 12th edition of the annual workshop series labeled “WebAndTheCity – The Web and Smart Cities”, which is the successor of the series of workshops that started in Florence in 2015 and has continued taking place every year in conjunction with the WWW conference series. Each year, the focus of the workshop is actualized, and this year, the workshop focuses on data-driven smart cities. In the era of IoT, AI, and agentic AI integration, the citiverse (metaverse for people-centric cities), cities are being transformed into urban environments that use data as a foundational asset to improve decision-making, optimize services, and enhance citizen well-being. At the same time, data is processed using various techniques and methods, which influence the outcomes. This workshop aims to explore how the Web supports this transformation and how technologies can improve smart cities.
Organizers: Leonidas Anthopoulos (Professor, University of Thessaly, Greece); Marijn Janssen (Professor, Delft University of Technology, The Netherlands); Vishanth Weerakkody (Professor, University of Bradford, United Kingdom)
Website: https://webandthecity.home.blog/
Description:
The recent achievements and availability of Large Language Models have paved the road to a new range of applications and use-cases. Pre-trained language models are now being involved at-scale across numerous fields, where they were previously unutilized. More specifically, the recent progress in generative models has paved the way to using them easily through textual instructions aka prompts. Unfortunately, the performances of these models are highly dependent on the exact phrasing used in prompts and therefore practitioners need to adopt fail-retry strategies.
This third international workshop on prompt engineering aims at gathering practitioners (both from Academia and Industry) to exchange about good practices, optimizations, results and novel paradigms about the designing of efficient prompts and context-building to make use of LLMs.
Organizers: Damien Graux (EcoVadis); Sébastien Montella (Huawei Technologies Ltd.); Hajira Jabeen (UniKlinik Cologne)
Website: https://prompteng-ws.github.io/2026/
Description: The recent growth of LLMs has expanded possibilities in data management, enabling powerful natural language access, reasoning, and decision support. However, reliability and trustworthiness remain major challenges when deploying LLMs in sensitive domains. Graph-based representations of knowledge and data (e.g., knowledge graphs and property graphs) provide a promising avenue to address these challenges. LLMs generate fluent responses but often struggle with factuality, bias, hallucinations, and a lack of explainability. Graphs, on the other hand, provide structured, interconnected representations that can serve as grounding and validation layers for LLM-based systems. Exploring the synergies between LLMs and graphs is critical to building data-driven applications where correctness and accountability are necessary.
Organizers: Gianluca Bonifazi (Marche Polytechnic University), Stefano Cirillo (University of Salerno), Eliana Pastor (Polytechnic University of Turin), Luca Virgili (Marche Polytechnic University)
Description:
Recommender systems shape how people discover information, form opinions, and connect with society. Yet, as their influence grows, traditional metrics—accuracy, clicks, and engagement—no longer capture what truly matters to humans. The workshop on Human-Centered Recommender Systems (HCRS) calls for a paradigm shift from optimizing engagement toward designing systems that truly understand, involve, and benefit people.
It brings together researchers in recommender systems, human-computer interaction, AI safety, and social computing to explore how human values such as trust, safety, fairness, transparency, and well-being can be integrated into recommendation processes. Centered around three thematic axes—Human Understanding, Human Involvement, and Human Impact—HCRS features keynotes, panels, and papers covering topics from LLM-based interactive recommenders to societal welfare optimization. By fostering interdisciplinary collaboration, HCRS aims to shape the next decade of responsible and human-aligned recommendation research.
Organizers: Kaike Zhang (University of Chinese Academy of Sciences, China), Jiakai Tang (Renmin University of China, China), Du Su (Institute of Computing Technology, Chinese Academy of Sciences, China), Shuchang Liu (Kuaishou Technology, China), Julian McAuley (University of California, San Diego, USA), Lina Yao (CSIRO Data61, Australia), Qi Cao (Institute of Computing Technology, Chinese Academy of Sciences, China), Yue Feng (University of Birmingham, UK), Fei Sun (University of Chinese Academy of Sciences, China)
Website: https://hcrec.github.io/
Description:
We propose a comprehensive half-day workshop (with at least 8 accepted papers, 3 keynote talks, and over 70 attendees) at WWW 2026, catering to professionals, researchers, and practitioners who are interested in sensing, mining, and understanding big and heterogeneous spatio-temporal data generated from the web (e.g., 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.
The workshop will not only offer a platform for knowledge exchange but also acknowledge outstanding contributions through a distinguished Best Paper Award. Furthermore, we envision the publication of accepted papers in a special issue organized in reputable journals such as ACM Transactions on Big Data and ACM Transactions on Intelligent Systems and Technology.
This workshop would be sponsored by JD Technology, with other committee members from MIT, CMU, UCB, etc. Note that this will be the fifth time that our core members have organized a similar workshop. The previous 14 workshops were hosted with SIGKDD, IJCAI, and WWW, each of which attracted over 70 participants and 30 submissions on average.
Organizers: Yuxuan Liang (The Hong Kong University of Science and Technology (Guangzhou)), Hao Xue (University of New South Wales), Ming Jin (Griffith University), Fei Wang (Institute of Computing Technology, Chinese Academy of Sciences), Qingxiang Liu (The Hong Kong University of Science and Technology (Guangzhou)), Qingsong Wen (Squirrel Ai Learning), Shirui Pan (Griffith University), Flora Salim (University of New South Wales)
Website: https://webst2026.netlify.app/
Description:
The ALTARS 2026 workshop explores recent advances and open challenges in Technology-Assisted Review (TAR) systems and their application to large-scale, high-recall retrieval across the Web. TAR systems, originally designed for domains such as legal discovery and systematic literature review, are now increasingly relevant in Web environments characterized by heterogeneous, dynamic, and multilingual information. As the Web continues to expand with both user-generated and AI-produced content, ensuring transparency, reliability, and fairness in automated review processes has become a central research challenge.
This workshop brings together researchers and practitioners from information retrieval, Web science, artificial intelligence, and data governance to discuss how TAR methodologies can support trustworthy and scalable information access. Topics include intelligent retrieval, human-in-the-loop learning, explainable and responsible AI, and the integration of large language models and knowledge graphs into review workflows. Through paper presentations, keynotes, and interactive sessions, ALTARS 2026 seeks to foster interdisciplinary collaboration and identify future directions for developing transparent, fair, and adaptive Web-scale review systems.
Organizers: Giorgio Maria Di Nunzio (University of Padova, Italy), Evangelos Kanoulas (University of Amsterdam, The Netherlands), Prasenjit Majumder (DAIICT, Gandhinagar, India)
Website: https://altars2026.dei.unipd.it/
Description:
With the rapid proliferation of social media platforms, the web has become a vast repository of diverse multimodal data, including text, images, audio, and video. This rich data offers unprecedented opportunities for comprehensive analysis but also introduces significant challenges in data fusion, information alignment, and robust processing. Large Multimodal Models (LMMs) have shown remarkable success in unimodal domains, yet their application to the complex and noisy nature of social media data necessitates significant innovation, particularly when such models are deployed on public-facing web platforms where performance, robustness, and safety are all critical.
The International Workshop on Trustworthy Multimodal Learning for Social Media Analysis (TML 2025) convenes researchers, practitioners, and industry experts to explore advances in multimodal social media content analysis with LMMs, multimodal fusion, information alignment, performance and safety evaluation, hallucination detection, jailbreak vulnerabilities, and the generation of safe content. By gathering interdisciplinary perspectives, the workshop aims to guide the development of responsible multimodal AI systems for the web ecosystem.
Organizers: Guosheng Lin (Nanyang Technological University (NTU), Singapore), Fengmao Lv (Southwest Jiaotong University, China), Jingwei Sun (ByteDance, China), Jianli Wang (Southwest Jiaotong University, China), Tao Liang (ByteDance, China)
Description:
The Future of Information Integrity Research (FIIR) Workshop explores the challenges and opportunities of ensuring reliable information in the era of generative AI. While these models can assist users in reasoning and information retrieval, they also introduce risks, including deepfakes, AI-driven persuasion, and large-scale manipulation of information flows. FIIR convenes researchers, practitioners, and policymakers to address these risks across four interconnected modules: Model Design (Core ML), Model Behaviour (Applied ML/AI Safety), Model Impact (Human Factors), and Model Ecosystem (Policy and Socio-Technical Systems).
The workshop features keynotes, expert panels, and breakout discussions designed to foster collaboration and bridge technical research with real-world practice, contributing frameworks and roadmaps for trustworthy information ecosystems.
Organizers: Taylor Lynn Curtis (Mila), Reihaneh Rabbany (McGill University, Mila), Hause Lin (Cornell, MIT, The World Bank), Maximilian Puelma Touzel (Mila), Kellin Pelrine (FAR.AI), Aisha Gurung (University of Bath), Catherine Régis (Mila, University of Montreal), Jean-François Godbout (Mila, University of Montreal), Nikki Lobczowski (McGill University), Bijean Ghafouri (University of Southern California)
Description:
The landscape of web advertising is undergoing a profound transformation, fueled by advancements in emerging technologies that prioritize user privacy, AI-driven personalization, and immersive experiences. As the digital advertising ecosystem evolves, understanding these trends is essential for navigating its dynamic complexities.
This workshop, organized by the Web Standards Group at Samsung Research and Development Institute UK (SRUK), provides a platform for timely, responsible, and open discussions among experts from advertising, privacy, data science, and related fields. Through cutting-edge research presentations and dialogue, the workshop aims to shape the future of web advertising while aligning technological progress with ethical and user-centric principles.
Organizers: Ehsan Toreini (Samsung Research and Development Institute UK), Muadh Al Kalbani (Samsung Research and Development Institute UK)
Website: TBD
Description:
The rapid proliferation of foundation models has transformed how information is processed, generated, and consumed on the web. From large language models powering conversational agents to multimodal systems driving content recommendation and retrieval, these models increasingly shape user experiences and web intelligence. Yet, their reliance on massive, uncurated web data raises critical concerns about trustworthiness, including bias propagation, lack of transparency, and vulnerability to manipulation.
This workshop aims to advance the discussion on Trustworthy Foundation Models for the Web by introducing a causal perspective—a principled approach to understanding and improving the reliability, interpretability, and fairness of large-scale models. It will convene experts from machine learning, causal inference, web data mining, and social computing to exchange ideas, present recent advances, and identify open challenges. By bridging causal reasoning with web-scale foundation models, the workshop seeks to establish a roadmap toward more robust, transparent, and ethically aligned AI systems that operate responsibly within the web ecosystem.
Organizers: Haoang Chi (Tsinghua University), Qi (Cheems) Wang (Tsinghua University), Jiangtong Jiang (The University of Melbourne), Jiangchao Yao (Shanghai Jiaotong University), Feng Liu (The University of Melbourne), Bo Han (Hong Kong Baptist University)
Description:
A full-day interactive workshop exploring how applied AI and multimodal visualization technologies can enhance knowledge representation, decision-making, and human–machine collaboration. It combines paper presentations with brainstorming sessions to foster collaboration and future research directions.
The workshop aims to:
• Showcase cutting-edge research and practical applications at the intersection of AI and multimodal visualization.
• Facilitate interdisciplinary dialogue between researchers, practitioners, and industry stakeholders.
• Explore methodologies and tools to improve human decision-making through multimodal data representation.
• Build collaborative networks to identify future research directions and applied use cases.
Organizers: Prof. Cesar Sanin (Australian Institute of Higher Education / University of New England, Australia), Prof. Edward Szczerbicki (University of Newcastle, Australia / Gdańsk University of Technology, Poland), Dr. Md Rafiqul Islam (Charles Darwin University, Australia)
Description:
The R2CASS workshop advances computational reproducibility in social science, often relying on digital behavioral data from social media platforms. It brings together computer scientists, social scientists, behavioral analysts, and digital policy makers to discuss improvements that make computational social science research more credible, reproducible, and impactful.
Building on the 1st R2CASS edition, this workshop assesses available resources—guidelines, checklists, templates—and services that support reproducibility practices. The workshop presents the Methods Hub as a case study, demonstrating how aligned resources and services can be integrated to lower reproducibility barriers.
Participants will take part in a hands-on session to perform a computational reproducibility task on the Methods Hub platform, followed by feedback discussions. By linking methodological rigor with substantive inquiry, the workshop encourages research related to computational reproducibility and social science.
Organizers: Fakhri Momeni (GESIS – Leibniz Institute for the Social Sciences, Germany), Arnim Bleier (GESIS – Leibniz Institute for the Social Sciences, Germany), Danilo Dessi (University of Sharjah, UAE), Muhammad Taimoor Khan (GESIS – Leibniz Institute for the Social Sciences, Germany)
Description:
In an increasingly interconnected world, where information flows rapidly through various digital platforms, multimodal content analysis has become an immense challenge. The prevalence of memes or text-embedded images has further complicated this issue, as it is often widely shared due to its engaging and easily consumable nature. Whether humorous or thought-provoking, these content forms can quickly go viral, spreading across social networks and online communities with ease.
Their visual appeal, concise messaging, and emotional resonance make them powerful tools for communication—shaping opinions and driving online conversations. However, this ease of sharing creates an urgent need for effective moderation. Moderating multimodal content requires sophisticated techniques capable of processing and understanding both visual and textual information simultaneously.
The Fourth International Workshop on Multimodal Content Analysis for Social Good (MM4SG 2026) aims to address these challenges by bringing together researchers from natural language processing, machine learning, computational social science, and ethics to explore innovative solutions for content moderation. The workshop provides a platform to share cutting-edge research, exchange ideas, and foster collaborations toward robust multimodal content analysis techniques.
Organizers: Usman Naseem (Macquarie University), Surendrabikram Thapa (Virginia Tech), Roy Ka-Wei Lee (Singapore University of Technology and Design), Mehwish Nasim (University of Western Australia)