Pratyush Maini

According to our database, Pratyush Maini authored at least 20 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Unlocking Post-hoc Dataset Inference with Synthetic Data.

Bihe Zhao, Pratyush Maini, Franziska Boenisch, Adam Dziedzic

CoRR, June, 2025

OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics.

Vineeth Dorna, Anmol Mekala, Wenlong Zhao, Andrew McCallum, Zachary C. Lipton, J. Zico Kolter, Pratyush Maini

CoRR, June, 2025

Safety Pretraining: Toward the Next Generation of Safe AI.

Pratyush Maini, Sachin Goyal, Dylan Sam, Alexander Robey, Yash Savani, Yiding Jiang, Andy Zou, Zacharcy C. Lipton, J. Zico Kolter

CoRR, April, 2025

STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings.

Saksham Rastogi, Pratyush Maini, Danish Pruthi

CoRR, April, 2025

Peeking Behind Closed Doors: Risks of LLM Evaluation by Private Data Curators.

Hritik Bansal, Pratyush Maini

CoRR, March, 2025

2024

TOFU: A Task of Fictitious Unlearning for LLMs.

Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary C. Lipton, J. Zico Kolter

CoRR, 2024

Rethinking LLM Memorization through the Lens of Adversarial Compression.

Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

LLM Dataset Inference: Did you train on my dataset?

Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Understanding Hallucinations in Diffusion Models through Mode Interpolation.

Sumukh K. Aithal, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

T-MARS: Improving Visual Representations by Circumventing Text Feature Learning.

Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J. Zico Kolter, Aditi Raghunathan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Scaling Laws for Data Filtering - Data Curation Cannot be Compute Agnostic.

Sachin Goyal, Pratyush Maini, Zachary C. Lipton, Aditi Raghunathan, J. Zico Kolter

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling.

Pratyush Maini, Skyler Seto, Richard He Bai, David Grangier, Yizhe Zhang, Navdeep Jaitly

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Can Neural Network Memorization Be Localized?

Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang

Proceedings of the International Conference on Machine Learning, 2023

Model-tuning Via Prompts Makes NLP Models Adversarially Robust.

Mrigank Raman, Pratyush Maini, J. Zico Kolter, Zachary C. Lipton, Danish Pruthi

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Perturbation type categorization for multiple adversarial perturbation robustness.

Pratyush Maini, Xinyun Chen, Bo Li, Dawn Song

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Characterizing Datapoints via Second-Split Forgetting.

Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Dataset Inference: Ownership Resolution in Machine Learning.

Pratyush Maini, Mohammad Yaghini, Nicolas Papernot

Proceedings of the 9th International Conference on Learning Representations, 2021

Data-Free Model Extraction.

Jean-Baptiste Truong, Pratyush Maini, Robert J. Walls, Nicolas Papernot

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Adversarial Robustness Against the Union of Multiple Perturbation Models.

Pratyush Maini, Eric Wong, J. Zico Kolter

Proceedings of the 37th International Conference on Machine Learning, 2020

Why and when should you pool? Analyzing Pooling in Recurrent Architectures.

Pratyush Maini, Keshav Kolluru, Danish Pruthi, Mausam

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020