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Fudan University
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Even state-of-the-art language models struggle significantly in real-world tasks, exposing critical shortcomings in their deployment readiness.
Learned critics in RLHF can actually *increase* variance and hurt performance in sparse-reward settings, but a simple explained variance metric can tell you when to ditch the critic and get better results.