Schwarzschild, Avi

28 publications

NeurIPS 2025 Antidistillation Sampling Yash Savani, Asher Trockman, Zhili Feng, Yixuan Even Xu, Avi Schwarzschild, Alexander Robey, Marc Anton Finzi, J Zico Kolter

TMLR 2025 Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-Training Objective Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P Dickerson, Pin-Yu Chen, Jeff Bilmes

ICLRW 2025 Evaluating LLM Memorization Using Soft Token Sparsity Zhili Feng, Yixuan Even Xu, Pratyush Maini, Alexander Robey, Avi Schwarzschild, J Zico Kolter

NeurIPS 2025 Extrapolation by Association: Length Generalization Transfer in Transformers Ziyang Cai, Nayoung Lee, Avi Schwarzschild, Samet Oymak, Dimitris Papailiopoulos

ICLRW 2025 Has My System Prompt Been Used? Large Language Model Prompt Membership Inference Roman Levin, Valeriia Cherepanova, Abhimanyu Hans, Avi Schwarzschild, Tom Goldstein

ICML 2025 Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges Nayoung Lee, Ziyang Cai, Avi Schwarzschild, Kangwook Lee, Dimitris Papailiopoulos

ICLRW 2025 Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges Nayoung Lee, Ziyang Cai, Avi Schwarzschild, Kangwook Lee, Dimitris Papailiopoulos

NeurIPS 2024 Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Anima Anandkumar, Furong Huang

NeurIPSW 2024 Has My System Prompt Been Used? Large Language Model Prompt Membership Inference Roman Levin, Valeriia Cherepanova, Abhimanyu Hans, Avi Schwarzschild, Tom Goldstein

ICLR 2024 NEFTune: Noisy Embeddings Improve Instruction Finetuning Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein

NeurIPS 2024 Rethinking LLM Memorization Through the Lens of Adversarial Compression Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter

NeurIPSW 2024 Rethinking LLM Memorization Through the Lens of Adversarial Compression Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary Chase Lipton, J Zico Kolter

ICML 2024 Spotting LLMs with Binoculars: Zero-Shot Detection of Machine-Generated Text Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein

ICLRW 2024 TOFU: A Task of Fictitious Unlearning for LLMs Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary Chase Lipton, J Zico Kolter

NeurIPSW 2024 TOFU: A Task of Fictitious Unlearning for LLMs Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary Chase Lipton, J Zico Kolter

NeurIPS 2024 Transformers Can Do Arithmetic with the Right Embeddings Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein

ICMLW 2024 Transformers Can Do Arithmetic with the Right Embeddings Sean Michael McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein

NeurIPSW 2024 Transformers Can Do Arithmetic with the Right Embeddings Sean Michael McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein

ICLR 2024 Universal Guidance for Diffusion Models Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Roni Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein

ICLR 2023 Transfer Learning with Deep Tabular Models Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum

CVPRW 2023 Universal Guidance for Diffusion Models Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein

NeurIPS 2022 End-to-End Algorithm Synthesis with Recurrent Networks: Extrapolation Without Overthinking Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein

NeurIPSW 2022 SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training Gowthami Somepalli, Avi Schwarzschild, Micah Goldblum, C. Bayan Bruss, Tom Goldstein

ICLR 2022 The Uncanny Similarity of Recurrence and Depth Avi Schwarzschild, Arjun Gupta, Amin Ghiasi, Micah Goldblum, Tom Goldstein

NeurIPSW 2022 Transfer Learning with Deep Tabular Models Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum

NeurIPS 2021 Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein

ICML 2021 Just How Toxic Is Data Poisoning? a Unified Benchmark for Backdoor and Data Poisoning Attacks Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein

ICLR 2020 Truth or Backpropaganda? an Empirical Investigation of Deep Learning Theory Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein