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cs.CL2024
RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution
Jiahui Li, Lin Li, Tai-wei Chang +4
Reinforcement learning from human feedback (RLHF) offers a promising approach to aligning large language models (LLMs) with human preferences. Typically, a reward model is trained…
cs.CY2024★ 2 cited
Exploring Prosocial Irrationality for LLM Agents: A Social Cognition View
Xuan Liu, Jie Zhang, Haoyang Shang +3
Large language models (LLMs) have been shown to face hallucination issues due to the data they trained on often containing human bias; whether this is reflected in the decision-mak…