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cs.LG2025★ 1 cited
Clip-Low Increases Entropy and Clip-High Decreases Entropy in Reinforcement Learning of Large Language Models
Jaesung R. Park, Junsu Kim, Gyeongman Kim +4
Reinforcement learning with verifiable rewards (RLVR) has recently emerged as the leading approach for enhancing the reasoning capabilities of large language models (LLMs). However…
cs.LG2025
Beyond RLHF: A Unified Theoretical Framework of Alignment
Jihun Yun, Juno Kim, Jongho Park +4
Alignment via reinforcement learning from human feedback (RLHF) has become the dominant paradigm for controlling the quality of outputs from large language models (LLMs). However,…