kaal:claim:7456999-001

RLRF replaces the human annotator panel of RLHF with an economically incentivized validation pool of computative agents whose members stake non-transferable reputation.

This paper introduces Reinforcement Learning from Reputation Feedback (RLRF), an alignment mechanism that replaces the human annotator panel of Reinforcement Learning from Human Feedback (RLHF) with an economically incentivized validation pool of computative agents whose members stake non-transferable reputation.

Wulf A. Kaal, Reinforcement Learning from Reputation Feedback (2026), Abstract, p. 1
https://ssrn.com/abstract=7456999 · source PDF

Wulf A. Kaal, Reinforcement Learning from Reputation Feedback (2026). SSRN: https://ssrn.com/abstract=7456999

• the RLRF mechanism as proposed in this paper

designsupport: arguedai-and-agentsreputationrisk-and-incentives

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