AINeutralarXiv – CS AI · 10h ago6/10
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PrivacyAlign: Contextual Privacy Alignment for LLM Agents
Researchers introduce PrivacyAlign, a dataset and training methodology that improves how large language model agents handle privacy decisions by grounding them in human judgment. The work demonstrates that conditioning LLM judges on human annotations and using annotation-based reward modeling produces agents better aligned with actual user privacy expectations across diverse scenarios.