Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control | ScienceToStartup | ScienceToStartup

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References (53)

[1]

Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning

2024Chenglin Li, Guangchun Ruan et al.

[2]

Rule Based Rewards for Language Model Safety

2024Tong Mu, Alec Helyar et al.

[3]

Distributional Preference Alignment of LLMs via Optimal Transport

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"A novel framework for safe reinforcement learning that enhances risk sensitivity through stochastic dominance."

Reinforcement Learning•Score: 4•View PDF ↗

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Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control

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Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control

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References (53)

Founder's Pitch

"A novel framework for safe reinforcement learning that enhances risk sensitivity through stochastic dominance."

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