Mark Ibrahim

According to our database, Mark Ibrahim authored at least 36 papers between 2017 and 2024.

Collaborative distances:

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

2024

UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling.

Haider Al-Tahan, Quentin Garrido, Randall Balestriero, Diane Bouchacourt, Caner Hazirbas, Mark Ibrahim

CoRR, 2024

𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs.

Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun

CoRR, 2024

Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?

Mark Ibrahim, David A. Klindt, Randall Balestriero

CoRR, 2024

The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More.

Ouail Kitouni, Niklas Nolte, Diane Bouchacourt, Adina Williams, Mike Rabbat, Mark Ibrahim

CoRR, 2024

An Introduction to Vision-Language Modeling.

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

CoRR, 2024

Modeling Caption Diversity in Contrastive Vision-Language Pretraining.

Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mahmoud Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas

CoRR, 2024

Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations.

Christian Tomani, Kamalika Chaudhuri, Ivan Evtimov, Daniel Cremers, Mark Ibrahim

CoRR, 2024

The Bias of Harmful Label Associations in Vision-Language Models.

Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark Ibrahim

CoRR, 2024

Discovering Environments with XRM.

Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Modeling Caption Diversity in Contrastive Vision-Language Pretraining.

Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data?

Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Embracing Diversity: Interpretable Zero-shot Classification Beyond One Vector Per Class.

Mazda Moayeri, Michael Rabbat, Mark Ibrahim, Diane Bouchacourt

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023

The Robustness Limits of SoTA Vision Models to Natural Variation.

Mark Ibrahim, Quentin Garrido, Ari S. Morcos, Diane Bouchacourt

Trans. Mach. Learn. Res., 2023

WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models.

Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, Jean-Baptiste Gaya, Xavier Martinet, Grégoire Mialon, Thomas Scialom, Emmanuel Dupoux, Dieuwke Hupkes, Pascal Vincent

CoRR, 2023

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations.

Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim

CoRR, 2023

Does Progress On Object Recognition Benchmarks Improve Real-World Generalization?

Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim

CoRR, 2023

A Cookbook of Self-Supervised Learning.

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

CoRR, 2023

Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies.

Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim

CoRR, 2023

Understanding the detrimental class-level effects of data augmentation.

Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Shanmukha Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations.

Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning.

Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

VPA: Fully Test-Time Visual Prompt Adaptation.

Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Disentanglement of Correlated Factors via Hausdorff Factorized Support.

Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations.

Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others.

Zhiheng Li, Ivan Evtimov, Albert Gordo, Caner Hazirbas, Tal Hassner, Cristian Canton-Ferrer, Chenliang Xu, Mark Ibrahim

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

RidgeSketch: A Fast Sketching Based Solver for Large Scale Ridge Regression.

Nidham Gazagnadou, Mark Ibrahim, Robert M. Gower

SIAM J. Matrix Anal. Appl., September, 2022

Robust Self-Supervised Learning with Lie Groups.

Mark Ibrahim, Diane Bouchacourt, Ari S. Morcos

CoRR, 2022

2021

Addressing the Topological Defects of Disentanglement via Distributed Operators.

Diane Bouchacourt, Mark Ibrahim, Stéphane Deny

CoRR, 2021

CrypTen: Secure Multi-Party Computation Meets Machine Learning.

Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Grounding inductive biases in natural images: invariance stems from variations in data.

Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Mixed membership recurrent neural networks for modeling customer purchases.

Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley

Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

2019

Global Explanations of Neural Networks: Mapping the Landscape of Predictions.

Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Mixed Membership Recurrent Neural Networks.

Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley

CoRR, 2018

Towards Explainable Deep Learning for Credit Lending: A Case Study.

Ceena Modarres, Mark Ibrahim, Melissa Louie, John W. Paisley

CoRR, 2018

2017

Connecting every bit of knowledge: The structure of Wikipedia's First Link Network.

Mark Ibrahim, Christopher M. Danforth, Peter Sheridan Dodds

J. Comput. Sci., 2017