arXiv · 2312.01057
RLHF and IIA: Perverse Incentives
Abstract
Existing algorithms for reinforcement learning from human feedback (RLHF) can incentivize responses at odds with preferences because they are based on models that assume independence of irrelevant alternatives (IIA). The perverse incentives induced by IIA hinder innovations on query formats and learning algorithms.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Wanqiao Xu, Shi Dong, Xiuyuan Lu, Grace Lam, Zheng Wen, Benjamin Van Roy. 2023-12-02. RLHF and IIA: Perverse Incentives. https://arxiv.org/abs/2312.01057
Cite the original work for its findings. Save a collection to share your selection of sources.