Schwarzschild, Avi

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

Goldblum, M., Tsipras, D., Xie, C., Chen, X., Schwarzschild, A., Song, D., Madry, A., Li, B., & Goldstein, T. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 362

A Cookbook of Self-Supervised Learning

Balestriero, R., Ibrahim, M., Sobal, V., Morcos, A., Shekhar, S., Goldstein, T., Bordes, F., Bardes, A., Mialon, G., Tian, Y., et al. (2023) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 182

Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

Hans, A., Schwarzschild, A., Cherepanova, V., Kazemi, H., Saha, A., Goldblum, M., Geiping, J., & Goldstein, T. (2024) · arXiv

Authorship Attribution and ProfilingDigital Media Forensic Detection

Cited by 24

Rethinking LLM Memorization through the Lens of Adversarial Compression

Schwarzschild, A., Feng, Z., Maini, P., Lipton, Z. C., & Kolter, J. Z. (2024) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 5

Antidistillation Sampling

Savani, Y., Trockman, A., Feng, Z., Xu, Y. E., Schwarzschild, A., Robey, A., Finzi, M., & Kolter, J. Z. (2025) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 1

Forcing diffuse distributions out of language models

Zhang, Y., Schwarzschild, A., Carlini, N., Kolter, Z., & Ippolito, D. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0