2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium
Xie Yi, Zhanke Zhou, Chentao Cao +3
Multi-agent frameworks can substantially boost the reasoning power of large language models (LLMs), but they typically incur heavy computational costs and lack convergence guarante…
cs.CV2023★ 2 cited
Improving Generalization in Visual Reinforcement Learning via Conflict-aware Gradient Agreement Augmentation
Siao Liu, Zhaoyu Chen, Yang Liu +8
Learning a policy with great generalization to unseen environments remains challenging but critical in visual reinforcement learning. Despite the success of augmentation combinatio…