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ORCIDMitchell Wortsman
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2020 – today
- 2025
[c24]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Luca Soldaini, Jenia Jitsev, Alex Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, et al.:
Language models scale reliably with over-training and on downstream tasks. ICLR 2025- 2024
- [b1]Mitchell Wortsman:
Robust and reliable large-scale transfer learning. University of Washington, USA, 2024 - [j2]Justin Chan
, Solomon Nsumba, Mitchell Wortsman, Achal Dave, Ludwig Schmidt, Shyamnath Gollakota, Kelly E. Michaelsen:
Detecting clinical medication errors with AI enabled wearable cameras. npj Digit. Medicine 7(1) (2024) - [c23]Dirk Groeneveld, Iz Beltagy, Evan Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. ACL (1) 2024: 15789-15809 - [c22]Mitchell Wortsman, Peter J. Liu, Lechao Xiao, Katie E. Everett, Alexander A. Alemi, Ben Adlam, John D. Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith:
Small-scale proxies for large-scale Transformer training instabilities. ICLR 2024 - [c21]Katie E. Everett, Lechao Xiao, Mitchell Wortsman, Alexander A. Alemi, Roman Novak, Peter J. Liu, Izzeddin Gur, Jascha Sohl-Dickstein, Leslie Pack Kaelbling, Jaehoon Lee, Jeffrey Pennington:
Scaling Exponents Across Parameterizations and Optimizers. ICML 2024 - [c20]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. NeurIPS 2024 - [c19]Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon:
Resolving Discrepancies in Compute-Optimal Scaling of Language Models. NeurIPS 2024 - [i29]Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. CoRR abs/2402.00838 (2024) - [i28]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt:
Language models scale reliably with over-training and on downstream tasks. CoRR abs/2403.08540 (2024) - [i27]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. CoRR abs/2406.11794 (2024) - [i26]Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon:
Resolving Discrepancies in Compute-Optimal Scaling of Language Models. CoRR abs/2406.19146 (2024) - [i25]Katie Everett, Lechao Xiao, Mitchell Wortsman, Alexander A. Alemi, Roman Novak, Peter J. Liu, Izzeddin Gur, Jascha Sohl-Dickstein, Leslie Pack Kaelbling, Jaehoon Lee, Jeffrey Pennington:
Scaling Exponents Across Parameterizations and Optimizers. CoRR abs/2407.05872 (2024) - 2023
- [j1]Mitchell Wortsman, Suchin Gururangan, Shen Li, Ali Farhadi, Ludwig Schmidt, Michael G. Rabbat, Ari S. Morcos:
lo-fi: distributed fine-tuning without communication. Trans. Mach. Learn. Res. 2023 (2023) - [c18]Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev:
Reproducible Scaling Laws for Contrastive Language-Image Learning. CVPR 2023: 2818-2829 - [c17]Samir Yitzhak Gadre, Mitchell Wortsman, Gabriel Ilharco, Ludwig Schmidt, Shuran Song:
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation. CVPR 2023: 23171-23181 - [c16]Gabriel Ilharco, Marco Túlio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, Ali Farhadi:
Editing models with task arithmetic. ICLR 2023 - [c15]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023 - [c14]Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt:
Stable and low-precision training for large-scale vision-language models. NeurIPS 2023 - [i24]Rahim Entezari, Mitchell Wortsman, Olga Saukh, Moein Shariatnia, Hanie Sedghi, Ludwig Schmidt:
The Role of Pre-training Data in Transfer Learning. CoRR abs/2302.13602 (2023) - [i23]Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt:
Stable and low-precision training for large-scale vision-language models. CoRR abs/2304.13013 (2023) - [i22]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - [i21]Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Yitzhak Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, Ludwig Schmidt:
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models. CoRR abs/2308.01390 (2023) - [i20]Mitchell Wortsman, Jaehoon Lee, Justin Gilmer, Simon Kornblith:
Replacing softmax with ReLU in Vision Transformers. CoRR abs/2309.08586 (2023) - [i19]Mitchell Wortsman, Peter J. Liu, Lechao Xiao, Katie Everett, Alex Alemi, Ben Adlam, John D. Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith:
Small-scale proxies for large-scale Transformer training instabilities. CoRR abs/2309.14322 (2023) - 2022
- [c13]Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, Ludwig Schmidt:
Robust fine-tuning of zero-shot models. CVPR 2022: 7949-7961 - [c12]Anas Awadalla, Mitchell Wortsman, Gabriel Ilharco, Sewon Min, Ian Magnusson, Hannaneh Hajishirzi, Ludwig Schmidt:
Exploring The Landscape of Distributional Robustness for Question Answering Models. EMNLP (Findings) 2022: 5971-5987 - [c11]Alex Fang, Gabriel Ilharco, Mitchell Wortsman, Yuhao Wan, Vaishaal Shankar, Achal Dave, Ludwig Schmidt:
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP). ICML 2022: 6216-6234 - [c10]Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt:
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. ICML 2022: 23965-23998 - [c9]Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt:
Patching open-vocabulary models by interpolating weights. NeurIPS 2022 - [c8]Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt:
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. NeurIPS 2022 - [c7]Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev:
LAION-5B: An open large-scale dataset for training next generation image-text models. NeurIPS 2022 - [i18]Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt:
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. CoRR abs/2203.05482 (2022) - [i17]Samir Yitzhak Gadre, Mitchell Wortsman, Gabriel Ilharco, Ludwig Schmidt, Shuran Song:
CLIP on Wheels: Zero-Shot Object Navigation as Object Localization and Exploration. CoRR abs/2203.10421 (2022) - [i16]Alex Fang, Gabriel Ilharco, Mitchell Wortsman, Yuhao Wan, Vaishaal Shankar, Achal Dave, Ludwig Schmidt:
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP). CoRR abs/2205.01397 (2022) - [i15]Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt:
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. CoRR abs/2208.05516 (2022) - [i14]Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt:
Patching open-vocabulary models by interpolating weights. CoRR abs/2208.05592 (2022) - [i13]Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev:
LAION-5B: An open large-scale dataset for training next generation image-text models. CoRR abs/2210.08402 (2022) - [i12]Mitchell Wortsman, Suchin Gururangan, Shen Li, Ali Farhadi, Ludwig Schmidt, Michael G. Rabbat, Ari S. Morcos:
lo-fi: distributed fine-tuning without communication. CoRR abs/2210.11948 (2022) - [i11]Anas Awadalla, Mitchell Wortsman, Gabriel Ilharco, Sewon Min, Ian Magnusson, Hannaneh Hajishirzi, Ludwig Schmidt:
Exploring The Landscape of Distributional Robustness for Question Answering Models. CoRR abs/2210.12517 (2022) - [i10]Gabriel Ilharco, Marco Túlio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, Ali Farhadi:
Editing Models with Task Arithmetic. CoRR abs/2212.04089 (2022) - [i9]Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev:
Reproducible scaling laws for contrastive language-image learning. CoRR abs/2212.07143 (2022) - 2021
- [c6]Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari:
Learning Neural Network Subspaces. ICML 2021: 11217-11227 - [i8]Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari:
Learning Neural Network Subspaces. CoRR abs/2102.10472 (2021) - [i7]Mitchell Wortsman, Gabriel Ilharco, Mike Li, Jong Wook Kim, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, Ludwig Schmidt:
Robust fine-tuning of zero-shot models. CoRR abs/2109.01903 (2021) - 2020
- [c5]Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi, Ali Farhadi, Mohammad Rastegari:
What's Hidden in a Randomly Weighted Neural Network? CVPR 2020: 11890-11899 - [c4]Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. ICML 2020: 5544-5555 - [c3]Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi:
Supermasks in Superposition. NeurIPS 2020 - [i6]Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. CoRR abs/2002.03231 (2020) - [i5]Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi:
Supermasks in Superposition. CoRR abs/2006.14769 (2020) - [i4]Maxwell Van Gelder, Mitchell Wortsman, Kiana Ehsani:
Deconstructing the Structure of Sparse Neural Networks. CoRR abs/2012.00172 (2020)
2010 – 2019
- 2019
- [c2]Mitchell Wortsman, Kiana Ehsani, Mohammad Rastegari, Ali Farhadi, Roozbeh Mottaghi:
Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning. CVPR 2019: 6750-6759 - [c1]Mitchell Wortsman, Ali Farhadi, Mohammad Rastegari:
Discovering Neural Wirings. NeurIPS 2019: 2680-2690 - [i3]Mitchell Wortsman, Ali Farhadi, Mohammad Rastegari:
Discovering Neural Wirings. CoRR abs/1906.00586 (2019) - [i2]Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi, Ali Farhadi, Mohammad Rastegari:
What's Hidden in a Randomly Weighted Neural Network? CoRR abs/1911.13299 (2019) - 2018
- [i1]Mitchell Wortsman, Kiana Ehsani, Mohammad Rastegari, Ali Farhadi, Roozbeh Mottaghi:
Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning. CoRR abs/1812.00971 (2018)
Coauthor Index
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