publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2024

  1. Understanding Hallucinations in Diffusion Models through Mode Interpolation
    Sumukh K Aithal, Pratyush Maini, Zachary Chase Lipton, and J Zico Kolter
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
  2. LLM Dataset Inference: Did you train on my dataset?
    Pratyush Maini, Hengrui Jia, Nicolas Papernot, and Adam Dziedzic
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
  3. Rethinking LLM Memorization through the Lens of Adversarial Compression
    Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary Chase Lipton, and J Zico Kolter
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
  4. Scaling Laws for Data Filtering—Data Curation cannot be Compute Agnostic
    Sachin Goyal*, Pratyush Maini*, Zachary C Lipton, Aditi Raghunathan, and J Zico Kolter
    In Conference on Computer Vision and Pattern Recognition, 2024
  5. Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
    Pratyush Maini*, Skyler Seto*, Richard Bai, David Grangier, Yizhe Zhang, and Navdeep Jaitly
    In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Aug 2024
  6. TOFU: A Task of Fictitious Unlearning for LLMs
    Pratyush Maini*, Zhili Feng*, Avi Schwarzschild*, Zachary C. Lipton, and J. Zico Kolter
    In , Aug 2024

2023

  1. Can Neural Network Memorization Be Localized?
    Pratyush Maini, Michael C Mozer, Hanie Sedghi, Zachary C Lipton, J Zico Kolter, and Chiyuan Zhang
    In International Conference on Machine Learning, Aug 2023
  2. T-MARS: Improving Visual Representations by Circumventing Text Feature Learning
    Pratyush Maini*, Sachin Goyal*, Zachary C Lipton, J Zico Kolter, and Aditi Raghunathan
    In International Conference on Learning Representations, Aug 2023

2022

  1. Characterizing Datapoints via Second-Split Forgetting
    Pratyush Maini, Saurabh Garg, Zachary Chase Lipton, and J Zico Kolter
    In Advances in Neural Information Processing Systems, Aug 2022
    Award Nominee
  2. Perturbation Type Categorization for Multiple \ell_p Bounded Adversarial Robustness
    Pratyush Maini, Xinyun Chen, Bo Li, and Dawn Song
    In Proceedings of The 38th Uncertainty in Artificial Intelligence Conference, Aug 2022

2021

  1. Dataset Inference: Ownership Resolution in Machine Learning
    Pratyush Maini, Mohammad Yaghini, and Nicolas Papernot
    Aug 2021
    Spotlight Award
  2. Data-free model extraction
    Jean-Baptiste Truong*, Pratyush Maini*, Robert J Walls, and Nicolas Papernot
    In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, Aug 2021

2020

  1. Adversarial Robustness Against the Union of Multiple Perturbation Models
    Pratyush Maini, Eric Wong, and J. Zico Kolter
    In International Conference on Machine Learning, Aug 2020
  2. Why and when should you pool? Analyzing Pooling in Recurrent Architectures
    Pratyush Maini, Keshav Kolluru, Danish Pruthi, and  Mausam
    In Findings of the Association for Computational Linguistics: EMNLP, Aug 2020
    Also presented at BlackBoxNLP’20