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arXiv Machine Learning By Siddhesh Pawar, Chen Cecilia Liu, Anna Korhonen, Isabelle Augenstein

Unintended Side Effects of Value Training in LLMs

Read the original on arXiv Machine Learning →

The paper examines how fine‑tuning large language models (LLMs) for specific human values can unintentionally affect other, untrained values and broader behaviors. By adapting four instruction‑tuned LLMs to Hofstede’s value dimensions, the authors evaluate cross‑value transfer and observe side effects on risk preferences, social cognition, and safety traits. They conclude that post‑training value alignment should include comprehensive behavioral assessments and that further research is needed to determine the optimal placement of value training within the development pipeline.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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