Vaishaal Shankar

59 papers A* 19A 1B 2Journal 32Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality.
CoRR
Alex Fang, Hadi Pouransari, Matt Jordan, Alexander Toshev, Vaishaal Shankar, Ludwig Schmidt, Tom Gunter
2025 A* conf
Language models scale reliably with over-training and on downstream tasks.
ICLR
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.
2025 J jnl
MobileCLIP2: Improving Multi-Modal Reinforced Training.
CoRR
Fartash Faghri, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Alexander Toshev, Oncel Tuzel, Hadi Pouransari
2025 J jnl
MobileCLIP2: Improving Multi-Modal Reinforced Training.
Trans. Mach. Learn. Res.
Fartash Faghri, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Alexander T. Toshev, Oncel Tuzel, Hadi Pouransari
2025 J jnl
OpenThoughts: Data Recipes for Reasoning Models.
CoRR
Etash Kumar Guha, Ryan Marten, Sedrick Keh, Negin Raoof, Georgios Smyrnis, Hritik Bansal, Marianna Nezhurina, Jean Mercat, Trung Vu, Zayne Sprague, Ashima Suvarna, Benjamin Feuer, Liangyu Chen, Zaid Khan, Eric Frankel, Sachin Grover, Caroline Choi, Niklas Muennighoff, Shiye Su, Wanjia Zhao, John Yang, Shreyas Pimpalgaonkar, Kartik Sharma, Charlie Cheng-Jie Ji, Yichuan Deng, Sarah M. Pratt, Vivek Ramanujan, Jon Saad-Falcon, Jeffrey Li, Achal Dave, Alon Albalak, Kushal Arora, Blake Wulfe, Chinmay Hegde, Greg Durrett, Sewoong Oh, Mohit Bansal, Saadia Gabriel, Aditya Grover, Kai-Wei Chang, Vaishaal Shankar, Aaron Gokaslan, Mike A. Merrill, Tatsunori Hashimoto, Yejin Choi, Jenia Jitsev, Reinhard Heckel, Maheswaran Sathiamoorthy, Alexandros G. Dimakis, Ludwig Schmidt
2025 — conf
TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining.
ACL (1)
Jeffrey Li, Mohammadreza Armandpour, Iman Mirzadeh, Sachin Mehta, Vaishaal Shankar, Raviteja Vemulapalli, Samy Bengio, Oncel Tuzel, Mehrdad Farajtabar, Hadi Pouransari, Fartash Faghri
2025 J jnl
TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining.
CoRR
Jeffrey Li, Mohammadreza Armandpour, Iman Mirzadeh, Sachin Mehta, Vaishaal Shankar, Raviteja Vemulapalli, Samy Bengio, Oncel Tuzel, Mehrdad Farajtabar, Hadi Pouransari, Fartash Faghri
2024 A* conf
Data Filtering Networks.
ICLR
Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T. Toshev, Vaishaal Shankar
2024 A* conf
DataComp-LM: In search of the next generation of training sets for language models.
NeurIPS
Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar 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
2024 J jnl
DataComp-LM: In search of the next generation of training sets for language models.
CoRR
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
2024 A* conf
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum.
NeurIPS
Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel
2024 J jnl
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum.
CoRR
Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel
2024 J jnl
Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts.
Trans. Mach. Learn. Res.
Jonathan Crabbé, Pau Rodríguez, Vaishaal Shankar, Luca Zappella, Arno Blaas
2024 J jnl
Language models scale reliably with over-training and on downstream tasks.
CoRR
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
2024 A* conf
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation.
EMNLP
Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev
2024 A* conf
Scalable Pre-training of Large Autoregressive Image Models.
ICML
Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Vaishaal Shankar, Alexander T. Toshev, Joshua M. Susskind, Armand Joulin
2024 J jnl
Scalable Pre-training of Large Autoregressive Image Models.
CoRR
Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Alexander Toshev, Vaishaal Shankar, Joshua M. Susskind, Armand Joulin
2024 A* conf
TiC-CLIP: Continual Training of CLIP Models.
ICLR
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri
2023 J jnl
Data Filtering Networks.
CoRR
Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander Toshev, Vaishaal Shankar
2023 A* conf
DataComp: In search of the next generation of multimodal datasets.
NeurIPS
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
2023 J jnl
DataComp: In search of the next generation of multimodal datasets.
CoRR
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
2023 A* conf
Masked Autoencoding Does Not Help Natural Language Supervision at Scale.
CVPR
Floris Weers, Vaishaal Shankar, Angelos Katharopoulos, Yinfei Yang, Tom Gunter
2023 J jnl
On Robustness in Multimodal Learning.
CoRR
Brandon McKinzie, Joseph Yitan Cheng, Vaishaal Shankar, Yinfei Yang, Jonathon Shlens, Alexander Toshev
2023 — conf
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation.
ICBINB
Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev
2023 J jnl
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation.
CoRR
Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev
2023 J jnl
Robust multimodal models have outlier features and encode more concepts.
CoRR
Jonathan Crabbé, Pau Rodríguez, Vaishaal Shankar, Luca Zappella, Arno Blaas
2023 A* conf
Robustness in Multimodal Learning under Train-Test Modality Mismatch.
ICML
Brandon McKinzie, Vaishaal Shankar, Joseph Yitan Cheng, Yinfei Yang, Jonathon Shlens, Alexander T. Toshev
2023 J jnl
Self Supervision Does Not Help Natural Language Supervision at Scale.
CoRR
Floris Weers, Vaishaal Shankar, Angelos Katharopoulos, Yinfei Yang, Tom Gunter
2023 J jnl
TiC-CLIP: Continual Training of CLIP Models.
CoRR
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri
2022 A* conf
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP).
ICML
Alex Fang, Gabriel Ilharco, Mitchell Wortsman, Yuhao Wan, Vaishaal Shankar, Achal Dave, Ludwig Schmidt
2022 J jnl
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP).
CoRR
Alex Fang, Gabriel Ilharco, Mitchell Wortsman, Yuhao Wan, Vaishaal Shankar, Achal Dave, Ludwig Schmidt
2021 J jnl
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization.
CoRR
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
2021 A* conf
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization.
ICML
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
2021 A* conf
Do Image Classifiers Generalize Across Time?
ICCV
Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt
2021 A* conf
Predicting with Confidence on Unseen Distributions.
ICCV
Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt
2021 J jnl
Predicting with Confidence on Unseen Distributions.
CoRR
Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt
2020 J jnl
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery.
CoRR
Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang
2020 A* conf
Evaluating Machine Accuracy on ImageNet.
ICML
Vaishaal Shankar, Rebecca Roelofs, Horia Mania, Alex Fang, Benjamin Recht, Ludwig Schmidt
2020 A* conf
Measuring Robustness to Natural Distribution Shifts in Image Classification.
NeurIPS
Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt
2020 J jnl
Measuring Robustness to Natural Distribution Shifts in Image Classification.
CoRR
Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt
2020 A* conf
Neural Kernels Without Tangents.
ICML
Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht
2020 J jnl
Neural Kernels Without Tangents.
CoRR
Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Ludwig Schmidt, Jonathan Ragan-Kelley, Benjamin Recht
2020 A conf
Serverless Straggler Mitigation using Error-Correcting Codes.
ICDCS
Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran
2020 J jnl
Serverless Straggler Mitigation using Local Error-Correcting Codes.
CoRR
Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran
2020 — conf
Serverless linear algebra.
SoCC
Vaishaal Shankar, Karl Krauth, Kailas Vodrahalli, Qifan Pu, Benjamin Recht, Ion Stoica, Jonathan Ragan-Kelley, Eric Jonas, Shivaram Venkataraman
2019 A* conf
A Meta-Analysis of Overfitting in Machine Learning.
NeurIPS
Rebecca Roelofs, Vaishaal Shankar, Benjamin Recht, Sara Fridovich-Keil, Moritz Hardt, John Miller, Ludwig Schmidt
2019 J jnl
A systematic framework for natural perturbations from videos.
CoRR
Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt
2019 J jnl
Cloud Programming Simplified: A Berkeley View on Serverless Computing.
CoRR
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
2019 A* conf
Do ImageNet Classifiers Generalize to ImageNet?
ICML
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar
2019 J jnl
Do ImageNet Classifiers Generalize to ImageNet?
CoRR
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar
2018 J jnl
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
CoRR
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar
2018 J jnl
numpywren: serverless linear algebra.
CoRR
Vaishaal Shankar, Karl Krauth, Qifan Pu, Eric Jonas, Shivaram Venkataraman, Ion Stoica, Benjamin Recht, Jonathan Ragan-Kelley
2017 J jnl
Flare Prediction Using Photospheric and Coronal Image Data.
CoRR
Eric Jonas, Monica G. Bobra, Vaishaal Shankar, J. Todd Hoeksema, Benjamin Recht
2017 J jnl
Ground Control to Major Tom: the importance of field surveys in remotely sensed data analysis.
CoRR
Ian Bolliger, Tamma Carleton, Solomon Hsiang, Jonathan Kadish, Jonathan Proctor, Benjamin Recht, Esther Rolf, Vaishaal Shankar
2016 — conf
Approximate Subgraph Isomorphism for Image Localization.
Image Processing: Algorithms and Systems
Vaishaal Shankar, Jordan Zhang, Jerry Chen, Christopher Dinh, Matthew Clements, Avideh Zakhor
2016 B conf
Reviewer Integration and Performance Measurement for Malware Detection.
DIMVA
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
2015 B conf
A Modern Student Experience inSystems Programming.
L@S
Vaishaal Shankar, David E. Culler
2015 J jnl
Back to the Future: Malware Detection with Temporally Consistent Labels.
CoRR
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
2015 — conf
Better Malware Ground Truth: Techniques for Weighting Anti-Virus Vendor Labels.
AISec@CCS
Alex Kantchelian, Michael Carl Tschantz, Sadia Afroz, Brad Miller, Vaishaal Shankar, Rekha Bachwani, Anthony D. Joseph, J. Doug Tygar