AI Research
Rank-Aware Differentially Private Release of Listwise Preferences for LLM Alignment
Listwise feedback brings richer alignment signals and greater privacy risks
Listwise preference feedback offers richer supervision for large language model (LLMs) alignment than pairwise comparisons, but a full ranking also reveals more sensitive user preferences.
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ArXiv CS.CL
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ArXiv CS.CL
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Generated insight by OnAirToday AI
Full rankings can provide richer feedback for aligning language models, but they also expose more about users’ preferences. Privacy-aware ways to release this feedback could help balance training utility with the protection of sensitive information.
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