About the Workshop
AI agents are becoming increasingly powerful and prevalent, interacting with the world on behalf of users and organizations. These systems raise foundational questions around reliability, adaptivity, personalization, strategic behavior, and learning from feedback in non-i.i.d. environments.
This workshop aims to bring together researchers in learning theory, online learning, game theory, statistical learning, and modern AI systems to develop rigorous frameworks for learning in the agentic era. Topics include learning with and from agents, strategic classification, performative prediction, multi-agent learning, verification and reliability, preference learning, personalization, and theory for LLM agents.
Keynote Speakers (Tentative)
Maria-Florina Balcan
Carnegie Mellon University
Nika Haghtalab
UC Berkeley
Yian Ma
UC San Diego
Tentative Schedule
| Duration | Activity |
|---|---|
| 30 minutes | Research Talk 1 |
| 30 minutes | Research Talk 2 |
| 30 minutes | Research Talk 3 |
| 60 minutes | Poster Session |
Call for Abstracts
We invite submissions of short abstracts, at most one page plus a link to a paper (optional but recommended), describing recent results, work in progress, or open problems related to the workshop themes. Accepted abstracts will be invited for poster presentation at the in-person workshop.
Relevant topics include, but are not limited to:
- Statistical learning with agents
- Strategic classification and performative prediction
- Multi-agent and game-theoretic learning
- Reliability, robustness, and verification in learning systems
- AI alignment, preference learning, and personalization
- Learning theory for LLM agents, including generation, reasoning, verification, and guidance
- Evaluation of LLMs and agentic systems
- Adaptive and online learning under agentic feedback and distribution shift
Email your submissions in PDF format to law2026colt@gmail.com . Submissions should use a font size of at least 10pt and margins of at least 1 inch.
Important Dates
| Abstract submission deadline | June 1, 2026 |
| Notification of acceptance | June 8, 2026 |
| Workshop date | June 29, 2026 |
Organizers
Hedyeh Beyhaghi
University of Massachusetts Amherst
hbeyhaghi@umass.edu
Avrim Blum
Toyota Technological Institute at Chicago
avrim@ttic.edu
Han Shao
University of Maryland, College Park
hanshao@umd.edu
Dravyansh Sharma
Toyota Technological Institute at Chicago
dravy@ttic.edu
Registration
Participants should follow the COLT 2026 registration instructions once available. Please check back for updates.
Interested in attending?
Registration link and participation details will be posted here.
