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ORCIDShibani Santurkar
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Books and Theses
- 2021
[b1]Shibani Santurkar:
Machine Learning Beyond Accuracy: A Features Perspective On Model Generalization. Massachusetts Institute of Technology, USA, 2021
Journal Articles
- 2023
- [j1]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 Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan 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:
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023)
Conference and Workshop Papers
- 2023
- [c20]Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto:
Is a Caption Worth a Thousand Images? A Study on Representation Learning. ICLR 2023 - [c19]Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto:
Whose Opinions Do Language Models Reflect? ICML 2023: 29971-30004 - [c18]Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang:
Data Selection for Language Models via Importance Resampling. NeurIPS 2023 - 2022
- [c17]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. NeurIPS 2022 - 2021
- [c16]Shibani Santurkar, Dimitris Tsipras, Aleksander Madry:
BREEDS: Benchmarks for Subpopulation Shift. ICLR 2021 - [c15]Eric Wong, Shibani Santurkar, Aleksander Madry:
Leveraging Sparse Linear Layers for Debuggable Deep Networks. ICML 2021: 11205-11216 - [c14]Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. NeurIPS 2021: 23359-23373 - 2020
- [c13]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
Implementation Matters in Deep RL: A Case Study on PPO and TRPO. ICLR 2020 - [c12]Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
A Closer Look at Deep Policy Gradients. ICLR 2020 - [c11]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. ICML 2020: 2922-2932 - [c10]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. ICML 2020: 9625-9635 - 2019
- [c9]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry:
Robustness May Be at Odds with Accuracy. ICLR (Poster) 2019 - [c8]Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Adversarial Examples Are Not Bugs, They Are Features. NeurIPS 2019: 125-136 - [c7]Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Image Synthesis with a Single (Robust) Classifier. NeurIPS 2019: 1260-1271 - 2018
- [c6]Shibani Santurkar, Ludwig Schmidt, Aleksander Madry:
A Classification-Based Study of Covariate Shift in GAN Distributions. ICML 2018: 4487-4496 - [c5]Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry:
How Does Batch Normalization Help Optimization? NeurIPS 2018: 2488-2498 - [c4]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. NeurIPS 2018: 5019-5031 - [c3]Shibani Santurkar, David M. Budden, Nir Shavit:
Generative Compression. PCS 2018: 258-262 - 2017
- [c2]David M. Budden, Alexander Matveev, Shibani Santurkar, Shraman Ray Chaudhuri, Nir Shavit:
Deep Tensor Convolution on Multicores. ICML 2017: 615-624 - 2015
- [c1]Shibani Santurkar, Bipin Rajendran
:
C. elegans chemotaxis inspired neuromorphic circuit for contour tracking and obstacle avoidance. IJCNN 2015: 1-8
Informal and Other Publications
- 2023
- [i24]Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang:
Data Selection for Language Models via Importance Resampling. CoRR abs/2302.03169 (2023) - [i23]Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto:
Whose Opinions Do Language Models Reflect? CoRR abs/2303.17548 (2023) - 2022
- [i22]Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto:
Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning. CoRR abs/2207.07635 (2022) - [i21]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 Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan 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:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - 2021
- [i20]Eric Wong, Shibani Santurkar, Aleksander Madry:
Leveraging Sparse Linear Layers for Debuggable Deep Networks. CoRR abs/2105.04857 (2021) - [i19]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. CoRR abs/2106.03805 (2021) - [i18]Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. CoRR abs/2112.01008 (2021) - 2020
- [i17]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry:
Identifying Statistical Bias in Dataset Replication. CoRR abs/2005.09619 (2020) - [i16]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry:
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. CoRR abs/2005.11295 (2020) - [i15]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO. CoRR abs/2005.12729 (2020) - [i14]Shibani Santurkar, Dimitris Tsipras, Aleksander Madry:
BREEDS: Benchmarks for Subpopulation Shift. CoRR abs/2008.04859 (2020) - 2019
- [i13]Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry:
Adversarial Examples Are Not Bugs, They Are Features. CoRR abs/1905.02175 (2019) - [i12]Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry:
Learning Perceptually-Aligned Representations via Adversarial Robustness. CoRR abs/1906.00945 (2019) - [i11]Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry:
Computer Vision with a Single (Robust) Classifier. CoRR abs/1906.09453 (2019) - 2018
- [i10]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. CoRR abs/1804.11285 (2018) - [i9]Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, Aleksander Madry:
How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift). CoRR abs/1805.11604 (2018) - [i8]Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry:
There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits). CoRR abs/1805.12152 (2018) - [i7]Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry:
Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms? CoRR abs/1811.02553 (2018) - 2017
- [i6]Shibani Santurkar, David M. Budden, Alexander Matveev, Heather Berlin, Hayk Saribekyan, Yaron Meirovitch, Nir Shavit:
Toward Streaming Synapse Detection with Compositional ConvNets. CoRR abs/1702.07386 (2017) - [i5]Shibani Santurkar, David M. Budden, Nir Shavit:
Generative Compression. CoRR abs/1703.01467 (2017) - [i4]Shibani Santurkar, Ludwig Schmidt, Aleksander Madry:
A Classification-Based Perspective on GAN Distributions. CoRR abs/1711.00970 (2017) - 2016
- [i3]David M. Budden, Alexander Matveev, Shibani Santurkar, Shraman Ray Chaudhuri, Nir Shavit:
Deep Tensor Convolution on Multicores. CoRR abs/1611.06565 (2016) - 2014
- [i2]Shibani Santurkar, Bipin Rajendran:
A neural circuit for navigation inspired by C. elegans Chemotaxis. CoRR abs/1410.7881 (2014) - [i1]Shibani Santurkar, Bipin Rajendran:
Sub-threshold CMOS Spiking Neuron Circuit Design for Navigation Inspired by C. elegans Chemotaxis. CoRR abs/1410.7883 (2014)
Coauthor Index
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