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PAC-Private Autoregressive Generation: Calibrating Noise to Ensemble Disagreement

This story is from 2026-09-09. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.05676v1 Announce Type: new Abstract: Language models adapted on private text are often served through APIs, so privacy leakage occurs through generated outputs rather than exposed weights. Private prediction protects these releases. Methods such as PMixED incur privacy cost at each relea…

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  1. 2026-09-09 04:00 · arXiv cs.LG
    PAC-Private Autoregressive Generation: Calibrating Noise to Ensemble Disagreement

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