5 papers · 1 filter
Coupled Variational Reinforcement Learning for Language Model General Reasoning
Xueru Wen, Jie Lou, Yanjiang Liu +6
While reinforcement learning has achieved impressive progress in language model reasoning, it is constrained by the requirement for verifiable rewards. Recent verifier-free RL meth…
MemSearcher: Training LLMs to Reason, Search and Manage Memory via End-to-End Reinforcement Learning
Qianhao Yuan, Jie Lou, Zichao Li +6
LLM-based search agents often concatenate the full interaction history into the context, producing long and noisy inputs, and increasing compute cost and GPU memory overhead. To ad…
PretrainZero: Reinforcement Active Pretraining
Xingrun Xing, Zhiyuan Fan, Jie Lou +3
Mimicking human behavior to actively learning from general experience and achieve artificial general intelligence has always been a human dream. Recent reinforcement learning (RL)…
Critic-CoT: Boosting the reasoning abilities of large language model via Chain-of-thoughts Critic
Xin Zheng, Jie Lou, Boxi Cao +7
Self-critic has become a crucial mechanism for enhancing the reasoning performance of LLMs. However, current approaches mainly involve basic prompts for intuitive instance-level fe…
Cheems: A Practical Guidance for Building and Evaluating Chinese Reward Models from Scratch
Xueru Wen, Jie Lou, Zichao Li +9
Reward models (RMs) are crucial for aligning large language models (LLMs) with human preferences. However, most RM research is centered on English and relies heavily on synthetic r…