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News/Bias Fitting to Mitigate Length Bias of Reward Model in RLHF
arxiv
PublishedJune 25, 2026 at 4:00 AM
—neutral

Bias Fitting to Mitigate Length Bias of Reward Model in RLHF

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2505.12843v2 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback (RLHF) relies on reward models to align large language models with human preferences. However, RLHF often suffers from reward hacking, wherein policy learning exploits flaws in the trained reward model to

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Discussion
Mentioned models
03
  • 01
    FiMi-RM
  • 02
    Direct Preference Optimization (DPO)
  • 03
    Best-of-N (BoN)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#reinforcement-learning#bias-mitigation#language-models

No replies yet. Be first.

Mentioned models
03
  • 01
    FiMi-RM
  • 02
    Direct Preference Optimization (DPO)
  • 03
    Best-of-N (BoN)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#reinforcement-learning#bias-mitigation#language-models

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