Call for Papers: ICLR 2026 Workshop on Multi-Agent Learning and Generative AI

[Caroline Wang]

Dear Colleagues,

We warmly invite you to submit your work to our ICLR 2026 Workshop on Multi-Agent Learning and Its Opportunities in the Era of Generative AI. Please see our website for full details.

About

The rapid emergence of generative AI has revitalized interest in multi-agent learning (MAL) as a foundation for building systems that can reason, coordinate, and adapt across diverse environments. This workshop explores the growing convergence between multi-agent learning and generative AI, emphasizing their mutual potential to advance both theoretical understanding and practical capability. Our goal is to ground the development of modern generative agents within the rigorous frameworks and knowledge of the multi-agent systems community.

Topics of Interest

We welcome submissions on topics including, but not limited to the following. Please see the call for papers on our website for full details.

• Multi-Agent Learning Paradigms for LLMs

• Generative AI for Multi-Agent Learning

• Multi-Agent Exploration for Generative AI

• Environments for Testing and Developing Multi-Agent Learning

• Human-AI Interaction

Important Dates

• Paper Submission Deadline: 5 February 2026, 11:59pm AOE

• Notification of Acceptance: 1 March 2026, 11:59pm AOE

• Camera-Ready Due: 3 April 2026, 11:59pm AOE

Confirmed Keynote Speakers

• Yali Du (King's College London)

• Eugene Vinitsky (New York University)

• Peter Stone (University of Texas at Austin and Sony AI)

• Natasha Jaques (University of Washington and Google DeepMind)

• Zhijing Jin (University of Toronto)

Tracks

Two tracks are offered. The workshop is non-archival.

• Main Research Track (6-8 pages excluding references and appendices): Full papers presenting novel methods, theoretical analyses, or comprehensive empirical results.

• Blueprint Papers Track (2-4 pages excluding references and appendices): ‘Tiny papers’ presenting preliminary research, exploratory/critical perspectives, or conceptual frameworks. This track particularly encourages submissions from newcomers, under-resourced researchers, and under-represented groups.

Submission and Review Process

• Submission Platform: All submissions will be managed through OpenReview. Submissions are required to use the provided workshop LaTeX template (download here). 

• Double-Blind Review: We enforce a double-blind review policy.

• Reviewer Assignment: Each submission will be evaluated by at least two members of the program committee with expertise in multi-agent learning, generative AI, or related fields.

• Final Decisions: Final acceptance decisions will be made by the organizing committee based on reviewer feedback and discussion..

• Conflict of Interest: We adhere to the ICLR policy on Conflicts of Interest (COI). Reviewers will be required to declare any potential conflicts, and conflicted papers will be reassigned.

• LLM Usage Policy: We will follow the official ICLR 2026 Policies on Large Language Model Usage.

Workshop Organizers

• Jianhong Wang (University of Bristol)

• Caroline Wang (UT Austin/Google DeepMind)

• Feng Chen (NTU)

• Muhammad Arrasy Rahman (UT Austin)

• Felipe Leno da Silva (LLNL)

• Rupali Bhati (Northeastern)

• Bo Liu (NUS)

• Mustafa Mert Çelikok (University of Southern Denmark)

We look forward to your contributions. For any inquiries, please contact iclr202...@gmail.com. To catch up with us, please follow us on X.

Best regards,

The Workshop Organizing Committee