7 citations · 14 across the 23 of their papers we have counts for
4 papers · 1 filter
HarnessNet: Feedback-driven Hierarchical Joint Harness Evolution for Multi-agent Systems
Zhaoyuan Qiu, Sachith Seneviratne, Yu Xia +1
AI agents can evolve by using environment feedback to revise their harnesses, the software managing model inputs, tool use, memory, and execution, while keeping foundation models f…
When Agents Disagree: Bayesian Backward Reasoning as a Label-Free Anchor for Multi-Agent Collective Decision-Making
Ken Chen, Wei Wang, Sachith Seneviratne +2
When multiple LLM agents yield conflicting answers, the decision-making process dictates whether agent diversity improves performance or merely compounds shared errors. Existing co…
HetGPS: Scalable Graph Multi-Agent Reinforcement Learning with Physics-Anchored Adaptive Safety for EV Charging
Xiangwei Wang, Nanduni Nimalsiri, Yu Xia +2
Safety interventions for large populations of network-coupled agents must protect shared constraints without unnecessarily overriding task-oriented policy decisions. We present Het…
Stepwise Intrinsic Rewards for Reasoning in Large Language Models
Xiangwei Wang, Wei Wang, Ken Chen +3
Reinforcement learning (RL) has become a widely used paradigm for improving the reasoning abilities of large language models (LLMs) and Vision-language models (VLMs). Sparse binary…