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Evidence record 4904 · automatically gathered

Misaligned by Reward: Socially Undesirable Preferences in LLMs

Reward models are a key component of large language model alignment, serving as proxies for human preferences during training. However, existing evaluations focus primarily on broad instruction-following benchmarks, providing limited insight into whether these models capture socially desirable preferences. As a result, important failures in social alignment can remain hidden. We extend reward-model benchmarking to four socially consequential domains: bias, safety, morality, and ethical reasoning

Record details

Published: 6 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness · Shared topic: Safety & alignment

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How to cite this record

ethics.ai (6 May 2026), “Misaligned by Reward: Socially Undesirable Preferences in LLMs,” evidence record 4904, https://ethics.ai/record/4904 (originally published by arXiv).

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