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cs.AI2025
Leveraging LLMs as Meta-Judges: A Multi-Agent Framework for Evaluating LLM Judgments
Yuran Li, Jama Hussein Mohamud, Chongren Sun +2
Large language models (LLMs) are being widely applied across various fields, but as tasks become more complex, evaluating their responses is increasingly challenging. Compared to h…
cs.AI2024
Robot Policy Learning with Temporal Optimal Transport Reward
Yuwei Fu, Haichao Zhang, Di Wu +2
Reward specification is one of the most tricky problems in Reinforcement Learning, which usually requires tedious hand engineering in practice. One promising approach to tackle thi…