Tsipras, Dimitris

17 publications

TMLR 2023 Holistic Evaluation of Language Models Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D Manning, Christopher Re, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Andrew Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

ICML 2022 Combining Diverse Feature Priors Saachi Jain, Dimitris Tsipras, Aleksander Madry

NeurIPS 2022 What Can Transformers Learn In-Context? a Case Study of Simple Function Classes Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant

ICLR 2021 BREEDS: Benchmarks for Subpopulation Shift Shibani Santurkar, Dimitris Tsipras, Aleksander Madry

NeurIPS 2021 Editing a Classifier by Rewriting Its Prediction Rules Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry

ICLR 2020 A Closer Look at Deep Policy Gradients Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

ICML 2020 From ImageNet to Image Classification: Contextualizing Progress on Benchmarks Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry

ICML 2020 Identifying Statistical Bias in Dataset Replication Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry

ICLR 2020 Implementation Matters in Deep RL: A Case Study on PPO and TRPO Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

Distill 2019 A Discussion of 'Adversarial Examples Are Not Bugs, They Are Features' Logan Engstrom, Justin Gilmer, Gabriel Goh, Dan Hendrycks, Andrew Ilyas, Aleksander Madry, Reiichiro Nakano, Preetum Nakkiran, Shibani Santurkar, Brandon Tran, Dimitris Tsipras, Eric Wallace

NeurIPS 2019 Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry

ICML 2019 Exploring the Landscape of Spatial Robustness Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry

NeurIPS 2019 Image Synthesis with a Single (Robust) Classifier Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry

ICLR 2019 Robustness May Be at Odds with Accuracy Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry

NeurIPS 2018 Adversarially Robust Generalization Requires More Data Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry

NeurIPS 2018 How Does Batch Normalization Help Optimization? Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry

ICLR 2018 Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu