Author

Andrew Ilyas

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#machine learning Jul 2025

Optimizing Canaries for Privacy Auditing with Metagradient Descent

This work develops a method for optimizing the auditor's canary set to improve privacy auditing, leveraging recent work on metagradient optimization and demonstrates that in certain instances, using such optimized canaries can improve empirical lower bounds for differentially private image classification models by seve...

Matteo Boglioni, Terrance Liu, Andrew Ilyas et al. · arXiv.org · 7 citations · ⚡1

#machine learning Preprint Sep 2026

Data Attribution via Sketched Metadifferentiation

Two algorithms, MAGE and SPELL, suited for reconstruction and attribution respectively, are presented, that run on existing metagradient machinery at no extra cost and demonstrate strong performance over existing baselines across training scales and measurement budgets.

Yu-Xi Chen, Hamza Golubovic, Han Tong et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Corrupt Plans, Clean Traces: Evading Chain-of-Thought Monitoring with Plan Injection

It is found that planting harmful but benign-sounding reasoning in the actor's context can steer it to perform adversarial actions while evading monitors, an attack the authors term"plan injection".

Keertana Chidambaram, Andrew Ilyas, Vasilis Syrgkanis · 0 citations

Review Jun 2026

Using AI Agents to Automate Black-Box Audits of Personalization Algorithms at Scale

This work introduces a framework for black-box audits of personalization algorithms using generative AI agents as behavioral engines for synthetic accounts and establishes GenAI-based agents as a new tool for algorithmic auditing.

Alessandro Morosini, Sarah H. Cen, Andrew Ilyas et al. · arXiv.org · 0 citations