6 papers
EvoPolicyGym: Evaluating Autonomous Policy Evolution in Interactive Environments
Zhilin Wang, Han Song, Runzhe Zhan +13
Autonomous agents are increasingly expected to improve executable policies through feedback, yet existing evaluations often collapse this process into a final score or confound it…
EgoGuide: Egocentric Guidance for Efficient Robot-Free Demonstration Collection and Learning
Yue Xu, Mingtao Nie, Tianle Li +4
Robot learning from real-world demonstrations is currently constrained by data scaling. Universal Manipulation Interface (UMI) provides an efficient robot-free data collection inte…
Differentiable Evolutionary Reinforcement Learning
Sitao Cheng, Tianle Li, Xuhan Huang +2
Crafting effective reward signals remains a central challenge in Reinforcement Learning (RL), especially for complex reasoning tasks. Existing automated reward optimization methods…
AesRM: Improving Video Aesthetics with Expert-Level Feedback
Yujin Han, Yujie Wei, Yefei He +7
Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors and cinematic lighting, beyo…
Reshaping Reasoning in LLMs: A Theoretical Analysis of RL Training Dynamics through Pattern Selection
Xingwu Chen, Tianle Li, Difan Zou
While reinforcement learning (RL) demonstrated remarkable success in enhancing the reasoning capabilities of language models, the training dynamics of RL in LLMs remain unclear. In…
On the Robustness of Transformers against Context Hijacking for Linear Classification
Tianle Li, Chenyang Zhang, Xingwu Chen +2
Transformer-based Large Language Models (LLMs) have demonstrated powerful in-context learning capabilities. However, their predictions can be disrupted by factually correct context…