Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling | ScienceToStartup | ScienceToStartup

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References (58)

[1]

Eliminating Inductive Bias in Reward Models with Information-Theoretic Guidance

2025Zhuo Li, Pengyu Cheng et al.

[2]

APLOT: Robust Reward Modeling via Adaptive Preference Learning with Optimal Transport

2025Zhuo Li, Yuege Feng et al.

[3]

Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy

Founder's Pitch

"Develop a Bayesian Non-Negative Reward Model for robust and interpretable reward learning in reinforcement learning from human feedback, addressing reward hacking challenges."

Reinforcement Learning•Score: 5•View PDF ↗

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Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling

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Founder's Pitch

"Develop a Bayesian Non-Negative Reward Model for robust and interpretable reward learning in reinforcement learning from human feedback, addressing reward hacking challenges."

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Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling

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References (58)

Founder's Pitch

"Develop a Bayesian Non-Negative Reward Model for robust and interpretable reward learning in reinforcement learning from human feedback, addressing reward hacking challenges."

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