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2020 – today
- 2025
[i28]Alex Fang, Hadi Pouransari, Matt Jordan, Alexander Toshev, Vaishaal Shankar, Ludwig Schmidt, Tom Gunter:
Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality. CoRR abs/2503.07879 (2025)- 2024
- [c25]Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev:
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation. EMNLP 2024: 1281-1287 - [c24]Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T. Toshev, Vaishaal Shankar:
Data Filtering Networks. ICLR 2024 - [c23]Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri:
TiC-CLIP: Continual Training of CLIP Models. ICLR 2024 - [c22]Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Vaishaal Shankar, Alexander T. Toshev, Joshua M. Susskind, Armand Joulin:
Scalable Pre-training of Large Autoregressive Image Models. ICML 2024 - [c21]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 - [c20]Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel:
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. NeurIPS 2024 - [i27]Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Alexander Toshev, Vaishaal Shankar, Joshua M. Susskind, Armand Joulin:
Scalable Pre-training of Large Autoregressive Image Models. CoRR abs/2401.08541 (2024) - [i26]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) - [i25]Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel:
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. CoRR abs/2405.13226 (2024) - [i24]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) - [i23]Tom Gunter, Zirui Wang, Chong Wang, Ruoming Pang, Andy Narayanan, Aonan Zhang, Bowen Zhang, Chen Chen, Chung-Cheng Chiu, David Qiu, Deepak Gopinath, Dian Ang Yap, Dong Yin, Feng Nan, Floris Weers, Guoli Yin, Haoshuo Huang, Jianyu Wang, Jiarui Lu, John Peebles, Ke Ye, Mark Lee, Nan Du, Qibin Chen, Quentin Keunebroek, Sam Wiseman, Syd Evans, Tao Lei, Vivek Rathod, Xiang Kong, Xianzhi Du, Yanghao Li, Yongqiang Wang, Yuan Gao, Zaid Ahmed, Zhaoyang Xu, Zhiyun Lu, Al Rashid, Albin Madappally Jose, Alec Doane, Alfredo Bencomo, Allison Vanderby, Andrew Hansen, Ankur Jain, Anupama Mann Anupama, Areeba Kamal, Bugu Wu, Carolina Brum, Charlie Maalouf, Chinguun Erdenebileg, Chris Dulhanty, Dominik Moritz, Doug Kang, Eduardo Jimenez, Evan Ladd, Fangping Shi, Felix Bai, Frank Chu, Fred Hohman, Hadas Kotek, Hannah Gillis Coleman, Jane Li, Jeffrey P. Bigham, Jeffery Cao, Jeff Lai, Jessica Cheung, Jiulong Shan, Joe Zhou, John Li, Jun Qin, Karanjeet Singh, Karla Vega, Kelvin Zou, Laura Heckman, Lauren Gardiner, Margit Bowler, Maria Cordell, Meng Cao, Nicole Hay, Nilesh Shahdadpuri, Otto Godwin, Pranay Dighe, Pushyami Rachapudi, Ramsey Tantawi, Roman Frigg, Sam Davarnia, Sanskruti Shah, Saptarshi Guha, Sasha Sirovica, Shen Ma, Shuang Ma, Simon Wang, Sulgi Kim, Suma Jayaram, Vaishaal Shankar, Varsha Paidi, Vivek Kumar, Xin Wang, Xin Zheng, Walker Cheng:
Apple Intelligence Foundation Language Models. CoRR abs/2407.21075 (2024) - 2023
- [c19]Floris Weers, Vaishaal Shankar, Angelos Katharopoulos, Yinfei Yang, Tom Gunter:
Masked Autoencoding Does Not Help Natural Language Supervision at Scale. CVPR 2023: 23432-23444 - [c18]Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev:
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation. ICBINB 2023: 127-133 - [c17]Brandon McKinzie, Vaishaal Shankar, Joseph Yitan Cheng, Yinfei Yang, Jonathon Shlens, Alexander T. Toshev:
Robustness in Multimodal Learning under Train-Test Modality Mismatch. ICML 2023: 24291-24303 - [c16]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 - [i22]Floris Weers, Vaishaal Shankar, Angelos Katharopoulos, Yinfei Yang, Tom Gunter:
Self Supervision Does Not Help Natural Language Supervision at Scale. CoRR abs/2301.07836 (2023) - [i21]Brandon McKinzie, Joseph Yitan Cheng, Vaishaal Shankar, Yinfei Yang, Jonathon Shlens, Alexander Toshev:
On Robustness in Multimodal Learning. CoRR abs/2304.04385 (2023) - [i20]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) - [i19]Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander Toshev, Vaishaal Shankar:
Data Filtering Networks. CoRR abs/2309.17425 (2023) - [i18]Jonathan Crabbé
, Pau Rodríguez, Vaishaal Shankar, Luca Zappella, Arno Blaas:
Robust multimodal models have outlier features and encode more concepts. CoRR abs/2310.13040 (2023) - [i17]Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri:
TiC-CLIP: Continual Training of CLIP Models. CoRR abs/2310.16226 (2023) - [i16]Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev:
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation. CoRR abs/2311.16201 (2023) - 2022
- [c15]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 - [i15]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) - 2021
- [c14]Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt:
Predicting with Confidence on Unseen Distributions. ICCV 2021: 1114-1124 - [c13]Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt:
Do Image Classifiers Generalize Across Time? ICCV 2021: 9641-9649 - [c12]John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt:
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. ICML 2021: 7721-7735 - [i14]Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt:
Predicting with Confidence on Unseen Distributions. CoRR abs/2107.03315 (2021) - [i13]John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt:
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. CoRR abs/2107.04649 (2021) - 2020
- [c11]Vaishaal Shankar, Karl Krauth, Kailas Vodrahalli, Qifan Pu, Benjamin Recht, Ion Stoica, Jonathan Ragan-Kelley, Eric Jonas, Shivaram Venkataraman:
Serverless linear algebra. SoCC 2020: 281-295 - [c10]Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran:
Serverless Straggler Mitigation using Error-Correcting Codes. ICDCS 2020: 135-145 - [c9]Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht:
Neural Kernels Without Tangents. ICML 2020: 8614-8623 - [c8]Vaishaal Shankar, Rebecca Roelofs, Horia Mania, Alex Fang, Benjamin Recht, Ludwig Schmidt:
Evaluating Machine Accuracy on ImageNet. ICML 2020: 8634-8644 - [c7]Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt:
Measuring Robustness to Natural Distribution Shifts in Image Classification. NeurIPS 2020 - [i12]Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran:
Serverless Straggler Mitigation using Local Error-Correcting Codes. CoRR abs/2001.07490 (2020) - [i11]Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Ludwig Schmidt, Jonathan Ragan-Kelley, Benjamin Recht:
Neural Kernels Without Tangents. CoRR abs/2003.02237 (2020) - [i10]Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt:
Measuring Robustness to Natural Distribution Shifts in Image Classification. CoRR abs/2007.00644 (2020) - [i9]Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang:
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery. CoRR abs/2010.08168 (2020)
2010 – 2019
- 2019
- [c6]Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar:
Do ImageNet Classifiers Generalize to ImageNet? ICML 2019: 5389-5400 - [c5]Rebecca Roelofs, Vaishaal Shankar, Benjamin Recht, Sara Fridovich-Keil, Moritz Hardt, John Miller, Ludwig Schmidt:
A Meta-Analysis of Overfitting in Machine Learning. NeurIPS 2019: 9175-9185 - [i8]Eric Jonas, Johann Schleier-Smith, Vikram Sreekanti, Chia-Che Tsai, Anurag Khandelwal, Qifan Pu, Vaishaal Shankar, João Carreira, Karl Krauth, Neeraja Jayant Yadwadkar, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica, David A. Patterson:
Cloud Programming Simplified: A Berkeley View on Serverless Computing. CoRR abs/1902.03383 (2019) - [i7]Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar:
Do ImageNet Classifiers Generalize to ImageNet? CoRR abs/1902.10811 (2019) - [i6]Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt:
A systematic framework for natural perturbations from videos. CoRR abs/1906.02168 (2019) - 2018
- [i5]Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar:
Do CIFAR-10 Classifiers Generalize to CIFAR-10? CoRR abs/1806.00451 (2018) - [i4]Vaishaal Shankar, Karl Krauth, Qifan Pu, Eric Jonas, Shivaram Venkataraman, Ion Stoica, Benjamin Recht, Jonathan Ragan-Kelley:
numpywren: serverless linear algebra. CoRR abs/1810.09679 (2018) - 2017
- [i3]Eric Jonas, Monica G. Bobra, Vaishaal Shankar, J. Todd Hoeksema, Benjamin Recht:
Flare Prediction Using Photospheric and Coronal Image Data. CoRR abs/1708.01323 (2017) - [i2]Ian Bolliger, Tamma Carleton, Solomon Hsiang, Jonathan Kadish, Jonathan Proctor, Benjamin Recht, Esther Rolf, Vaishaal Shankar:
Ground Control to Major Tom: the importance of field surveys in remotely sensed data analysis. CoRR abs/1710.09342 (2017) - 2016
- [c4]Brad Miller, Alex Kantchelian, Michael Carl Tschantz, Sadia Afroz, Rekha Bachwani, Riyaz Faizullabhoy, Ling Huang, Vaishaal Shankar, Tony Wu, George Yiu, Anthony D. Joseph, J. D. Tygar:
Reviewer Integration and Performance Measurement for Malware Detection. DIMVA 2016: 122-141 - [c3]Vaishaal Shankar, Jordan Zhang, Jerry Chen, Christopher Dinh, Matthew Clements, Avideh Zakhor:
Approximate Subgraph Isomorphism for Image Localization. Image Processing: Algorithms and Systems 2016: 1-9 - 2015
- [c2]Alex Kantchelian, Michael Carl Tschantz, Sadia Afroz, Brad Miller, Vaishaal Shankar, Rekha Bachwani, Anthony D. Joseph, J. Doug Tygar:
Better Malware Ground Truth: Techniques for Weighting Anti-Virus Vendor Labels. AISec@CCS 2015: 45-56 - [c1]Vaishaal Shankar, David E. Culler:
A Modern Student Experience inSystems Programming. L@S 2015: 233-236 - [i1]Brad Miller, Alex Kantchelian, Michael Carl Tschantz, Sadia Afroz, Rekha Bachwani, Riyaz Faizullabhoy, Ling Huang, Vaishaal Shankar, Tony Wu, George Yiu, Anthony D. Joseph, J. D. Tygar:
Back to the Future: Malware Detection with Temporally Consistent Labels. CoRR abs/1510.07338 (2015)
Coauthor Index
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