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Journal Articles
- 2023
[j3]Mark Ibrahim, Quentin Garrido, Ari S. Morcos, Diane Bouchacourt:
The Robustness Limits of SoTA Vision Models to Natural Variation. Trans. Mach. Learn. Res. 2023 (2023)- 2022
- [j2]Nidham Gazagnadou, Mark Ibrahim, Robert M. Gower
:
RidgeSketch: A Fast Sketching Based Solver for Large Scale Ridge Regression. SIAM J. Matrix Anal. Appl. 43(3): 1440-1468 (2022) - 2017
- [j1]Mark Ibrahim, Christopher M. Danforth, Peter Sheridan Dodds:
Connecting every bit of knowledge: The structure of Wikipedia's First Link Network. J. Comput. Sci. 19: 21-30 (2017)
Conference and Workshop Papers
- 2024
- [c16]Mazda Moayeri, Michael Rabbat, Mark Ibrahim, Diane Bouchacourt:
Embracing Diversity: Interpretable Zero-shot Classification Beyond One Vector Per Class. FAccT 2024: 2302-2321 - [c15]Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim:
Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data? ICLR 2024 - [c14]Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas:
Modeling Caption Diversity in Contrastive Vision-Language Pretraining. ICML 2024 - [c13]Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz:
Discovering Environments with XRM. ICML 2024 - 2023
- [c12]Zhiheng Li, Ivan Evtimov, Albert Gordo, Caner Hazirbas, Tal Hassner, Cristian Canton-Ferrer, Chenliang Xu, Mark Ibrahim:
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others. CVPR 2023: 20071-20082 - [c11]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR 2023 - [c10]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. ICLR 2023 - [c9]Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas:
VPA: Fully Test-Time Visual Prompt Adaptation. ACM Multimedia 2023: 5796-5806 - [c8]Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos:
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. NeurIPS 2023 - [c7]Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein:
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. NeurIPS 2023 - [c6]Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim:
Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations. NeurIPS 2023 - [c5]Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Shanmukha Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson:
Understanding the detrimental class-level effects of data augmentation. NeurIPS 2023 - 2021
- [c4]Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten:
CrypTen: Secure Multi-Party Computation Meets Machine Learning. NeurIPS 2021: 4961-4973 - [c3]Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos:
Grounding inductive biases in natural images: invariance stems from variations in data. NeurIPS 2021: 19566-19579 - 2020
- [c2]Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley:
Mixed membership recurrent neural networks for modeling customer purchases. ICAIF 2020: 36:1-36:8 - 2019
- [c1]Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley:
Global Explanations of Neural Networks: Mapping the Landscape of Predictions. AIES 2019: 279-287
Informal and Other Publications
- 2024
- [i31]Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson:
Understanding the Detrimental Class-level Effects of Data Augmentation. CoRR abs/2401.01764 (2024) - [i30]Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark Ibrahim:
The Bias of Harmful Label Associations in Vision-Language Models. CoRR abs/2402.07329 (2024) - [i29]Christian Tomani, Kamalika Chaudhuri, Ivan Evtimov, Daniel Cremers, Mark Ibrahim:
Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations. CoRR abs/2404.10960 (2024) - [i28]Mazda Moayeri, Michael Rabbat, Mark Ibrahim, Diane Bouchacourt:
Embracing Diversity: Interpretable Zero-shot classification beyond one vector per class. CoRR abs/2404.16717 (2024) - [i27]Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mahmoud Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas:
Modeling Caption Diversity in Contrastive Vision-Language Pretraining. CoRR abs/2405.00740 (2024) - [i26]Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra:
An Introduction to Vision-Language Modeling. CoRR abs/2405.17247 (2024) - [i25]Ouail Kitouni, Niklas Nolte, Diane Bouchacourt, Adina Williams, Mike Rabbat, Mark Ibrahim:
The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More. CoRR abs/2406.05183 (2024) - [i24]Mark Ibrahim, David Klindt, Randall Balestriero:
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations? CoRR abs/2406.10743 (2024) - [i23]Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun:
𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. CoRR abs/2407.18134 (2024) - [i22]Haider Al-Tahan, Quentin Garrido, Randall Balestriero, Diane Bouchacourt, Caner Hazirbas, Mark Ibrahim:
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling. CoRR abs/2408.04810 (2024) - 2023
- [i21]Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim:
Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies. CoRR abs/2304.05391 (2023) - [i20]Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum:
A Cookbook of Self-Supervised Learning. CoRR abs/2304.12210 (2023) - [i19]Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim:
Does Progress On Object Recognition Benchmarks Improve Real-World Generalization? CoRR abs/2307.13136 (2023) - [i18]Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari S. Morcos:
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. CoRR abs/2308.03977 (2023) - [i17]Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas:
VPA: Fully Test-Time Visual Prompt Adaptation. CoRR abs/2309.15251 (2023) - [i16]Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz:
Discovering environments with XRM. CoRR abs/2309.16748 (2023) - [i15]Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein:
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. CoRR abs/2310.19909 (2023) - [i14]Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim:
Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations. CoRR abs/2311.08815 (2023) - [i13]Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, Jean-Baptiste Gaya, Xavier Martinet, Grégoire Mialon, Thomas Scialom, Emmanuel Dupoux, Dieuwke Hupkes, Pascal Vincent:
WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models. CoRR abs/2311.15930 (2023) - 2022
- [i12]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. CoRR abs/2210.07347 (2022) - [i11]Mark Ibrahim, Diane Bouchacourt, Ari S. Morcos:
Robust Self-Supervised Learning with Lie Groups. CoRR abs/2210.13356 (2022) - [i10]Mark Ibrahim, Quentin Garrido, Ari Morcos, Diane Bouchacourt:
The Robustness Limits of SoTA Vision Models to Natural Variation. CoRR abs/2210.13604 (2022) - [i9]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR abs/2211.01866 (2022) - [i8]Zhiheng Li, Ivan Evtimov, Albert Gordo, Caner Hazirbas, Tal Hassner, Cristian Canton-Ferrer, Chenliang Xu, Mark Ibrahim:
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others. CoRR abs/2212.04825 (2022) - 2021
- [i7]Diane Bouchacourt, Mark Ibrahim, Stéphane Deny:
Addressing the Topological Defects of Disentanglement via Distributed Operators. CoRR abs/2102.05623 (2021) - [i6]Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos:
Grounding inductive biases in natural images: invariance stems from variations in data. CoRR abs/2106.05121 (2021) - [i5]Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten:
CrypTen: Secure Multi-Party Computation Meets Machine Learning. CoRR abs/2109.00984 (2021) - 2019
- [i4]Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley:
Global Explanations of Neural Networks: Mapping the Landscape of Predictions. CoRR abs/1902.02384 (2019) - 2018
- [i3]Ceena Modarres, Mark Ibrahim, Melissa Louie, John W. Paisley:
Towards Explainable Deep Learning for Credit Lending: A Case Study. CoRR abs/1811.06471 (2018) - [i2]Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley:
Mixed Membership Recurrent Neural Networks. CoRR abs/1812.09645 (2018) - 2016
- [i1]Mark Ibrahim, Christopher M. Danforth, Peter Sheridan Dodds:
Connecting every bit of knowledge: The structure of Wikipedia's First Link Network. CoRR abs/1605.00309 (2016)
Coauthor Index
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