Covert Learning: How to Learn with an Untrusted Intermediary. - Ran Canetti; Ari Karchmer (IACR Cryptol. ePrint Arch., 2021)

The Limits of Provable Security Against Model Extraction. - Ari Karchmer (IACR Cryptol. ePrint Arch., 2022)

Theoretical Limits of Provable Security Against Model Extraction by Efficient Observational Defenses. - Ari Karchmer (SaTML, 2023)

Agnostic Membership Query Learning with Nontrivial Savings: New Results, Techniques. - Ari Karchmer (CoRR, 2023)

Average-Case PAC-Learning from Nisan's Natural Proofs. - Ari Karchmer (Electron. Colloquium Comput. Complex., 2023)

Agnostic Membership Query Learning with Nontrivial Savings: New Results and Techniques. - Ari Karchmer (ALT, 2024)

On Stronger Computational Separations Between Multimodal and Unimodal Machine Learning. - Ari Karchmer (ICML, 2024)

Distributional PAC-Learning from Nisan's Natural Proofs. - Ari Karchmer (ITCS, 2024)

The Power of Random Features and the Limits of Distribution-Free Gradient Descent. - Ari Karchmer; Eran Malach (CoRR, 2025)

Efficiently Verifiable Proofs of Data Attribution. - Ari Karchmer; Martin Pawelczyk; Seth Neel (CoRR, 2025)