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cs.LG2024
Entropy Controllable Direct Preference Optimization
Motoki Omura, Yasuhiro Fujita, Toshiki Kataoka
In the post-training of large language models (LLMs), Reinforcement Learning from Human Feedback (RLHF) is an effective approach to achieve generation aligned with human preference…
cs.LG2024★ 1 cited
Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning
Motoki Omura, Takayuki Osa, Yusuke Mukuta +1
In deep reinforcement learning, estimating the value function to evaluate the quality of states and actions is essential. The value function is often trained using the least square…