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Author

Sofiane Azogagh

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#artificial intelligence Preprint Sep 2026

Quantization Enables Private Dense Retrieval against Malicious Service Providers

The results suggest that private dense retrieval is already practical for moderately sized, privacy-sensitive corpora when minute-scale latency is acceptable, and formulates a two-round cryptographic protocol that provides both guarantees.

Louis Tremblay Thibault, Sofiane Azogagh, Marc-Olivier Killijian et al. · 0 citations
Preprint Aug 2026

Manipulation-Proof Oblivious Audits against Deceptive Model Providers

A novel audit protocol designed to significantly increase the post-audit detectability of manipulations by enabling the auditor to query the model in an oblivious manner and providing theoretical guarantees showing that, under this protocol, a provider attempting to hide unfairness must falsify a significantly larger n...

Augustin Godinot, Sofiane Azogagh, Julien Ferry et al. · 0 citations

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