arXiv AI
Jul 3

Who Gets the Reward & Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents

arXiv:2511. 10687v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) in multi-agent systems (MAS) have shown promise for complex tasks, yet current training methods lack principled ways to connect system-level evaluation with agent- and message-level learning.

By Chih-Hsuan (Bella), Yang, Tanwi Mallick, Le Chen, Krishnan Raghavan, Amal Gueroudji, Ian T. Foster, Rajeev Thakur
arXiv Machine Learning
5d ago

Narrowing the Collaboration Gap, Probably

arXiv:2610.19215v1 Announce Type: new Abstract: Large language models are increasingly deployed as teams of agents that hold different private information about a shared task. How should such agents...

By Mirah Shi, Marcel Hussing, Ira Globus-Harris, Natalie Collina, Aaron Roth, Surbhi Goel