43 citations · 53 across the 19 of their papers we have counts for
4 papers · 1 filter
Skill Reuse as Compression in Agentic RL
Zhikun Xu, Yu Feng, Jacob Dineen +3
Large language model agents trained with reinforcement learning (RL) often learn brittle, task-specific shortcuts. We hypothesize that agents generalize better when their successfu…
Experiential Reinforcement Learning
Taiwei Shi, Sihao Chen, Bowen Jiang +3
Reinforcement learning has become the central approach for language models (LMs) to learn from environmental reward or feedback. In practice, the environmental feedback is usually…
Efficient Reinforcement Finetuning via Adaptive Curriculum Learning
Taiwei Shi, Yiyang Wu, Linxin Song +2
Reinforcement finetuning (RFT) has shown great potential for enhancing the mathematical reasoning capabilities of large language models (LLMs), but it is often sample- and compute-…
Detecting and Filtering Unsafe Training Data via Data Attribution with Denoised Representation
Yijun Pan, Taiwei Shi, Jieyu Zhao +1
Large language models (LLMs) are highly sensitive to even small amounts of unsafe training data, making effective detection and filtering essential for trustworthy model developmen…