Creolizing the Web. - Abhinav Tamaskar; Roy Rinberg; Sunandan Chakraborty; Bud Mishra (CoRR, 2021)

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation. - Kaustubh D. Dhole; Varun Gangal; Sebastian Gehrmann; Aadesh Gupta; Zhenhao Li; Saad Mahamood; Abinaya Mahendiran; Simon Mille; Ashish Srivastava; Samson Tan; Tongshuang Wu; Jascha Sohl-Dickstein; et al. (CoRR, 2021)

Privacy when Everyone is Watching: An SOK on Anonymity on the Blockchain. - Roy Rinberg; Nilaksh Agarwal (IACR Cryptol. ePrint Arch., 2022)

Have it your way: Individualized Privacy Assignment for DP-SGD. - Franziska Boenisch; Christopher Mühl; Adam Dziedzic; Roy Rinberg; Nicolas Papernot (NeurIPS, 2023)

Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees. - Franziska Boenisch; Christopher Mühl; Roy Rinberg; Jannis Ihrig; Adam Dziedzic (Proc. Priv. Enhancing Technol., 2023)

Attribute-to-Delete: Machine Unlearning via Datamodel Matching. - Kristian Georgiev; Roy Rinberg; Sung Min Park; Shivam Garg; Andrew Ilyas; Aleksander Madry; Seth Neel (CoRR, 2024)

Machine Unlearning via Simulated Oracle Matching. - Kristian Georgiev; Roy Rinberg; Sung Min Park; Shivam Garg; Andrew Ilyas; Aleksander Madry; Seth Neel (ICLR, 2025)

Beyond Laplace and Gaussian: Exploring the Generalized Gaussian Mechanism for Private Machine Learning. - Roy Rinberg; Ilia Shumailov; Vikrant Singhal; Rachel Cummings; Nicolas Papernot (CoRR, 2025)