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Evidence record 4696 · automatically gathered

Latent Personality Alignment: Improving Harmlessness Without Mentioning Harms

Current adversarial robustness methods for large language models require extensive datasets of harmful prompts (thousands to hundreds of thousands of examples), yet remain vulnerable to novel attack vectors and distributional shifts. We propose Latent Personality Alignment (LPA), a sample-efficient defense that achieves robustness by training models on abstract personality traits rather than specific harmful behaviors. Using fewer than 100 trait statements and latent adversarial training, LPA ac

Record details

Published: 8 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Military & security
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.

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How to cite this record

ethics.ai (8 May 2026), “Latent Personality Alignment: Improving Harmlessness Without Mentioning Harms,” evidence record 4696, https://ethics.ai/record/4696 (originally published by arXiv).

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