Author

Aaron Roth

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#machine learning Preprint Oct 2026

Groupwise Distortion Guarantees for Preference-Based Alignment

Preference-based alignment methods such as reinforcement learning from human feedback (RLHF) and Nash learning from human feedback (NLHF) aggregate pairwise preferences to learn an LLM policy, but a natural goal is maximizing social welfare (average cardinal utility), which comparisons alone need not identify. G\"olz,...

Jacob Brodkey, Roberto Tamez, Aaron Roth · 0 citations

#artificial intelligence Review Sep 2026

Delegating Authorization to Misaligned Agents: Coalitional Alignment and Safe Control

This work identifies a condition on a reviewing panel that is weaker than individual alignment yet necessary and sufficient for a guarantee that the principal fares at least as well in expectation as under a designated baseline policy.

Natalie Collina, Surbhi Goel, Aaron Roth et al. · 0 citations