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Garry YANG

2 accepted papers

2026

Hista and Numca: Estimate State Value Effectively for Large Language Model Reinforcement Learning

ICML 2026spotlight

Reinforcement Learning (RL) refines large language models (LLMs) by directly optimizing model behavior with reward signals. Although accurate state value estimation is essential for stable training in classical RL settings, it remains an understudied challenge in LLM post-training. In this work, we …

Cited by 0SourceScholar
2026

Reducing Belief Deviation in Reinforcement Learning for Active Reasoning

ICLR 2026oral

Active reasoning requires large language models (LLMs) to interact with external sources and strategically gather information to solve problems. Central to this process is belief tracking: maintaining a coherent understanding of the problem state and the missing information toward the solution. Howe…

Cited by 0SourcecodeScholar