Vaishaal Shankar

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 45

Top Topics

Image Generation

Machine Learning

Top Venues

Publications

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 (2024)
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)
Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee 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 (2024)
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 (2024)
Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T. Toshev, Vaishaal Shankar
Data Filtering Networks. ICLR (2024)
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 (2024)
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 (2024)
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri
TiC-CLIP: Continual Training of CLIP Models. CoRR (2023)
Jonathan Crabbé, Pau Rodríguez, Vaishaal Shankar, Luca Zappella, Arno Blaas
Robust multimodal models have outlier features and encode more concepts. CoRR (2023)
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 (2023)
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)
Floris Weers, Vaishaal Shankar, Angelos Katharopoulos, Yinfei Yang, Tom Gunter
Masked Autoencoding Does Not Help Natural Language Supervision at Scale. CVPR (2023)
Yuhui Zhang, Brandon McKinzie, Zhe Gan, Vaishaal Shankar, Alexander Toshev
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation. CoRR (2023)
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)
Brandon McKinzie, Joseph Cheng, Vaishaal Shankar, Yinfei Yang, Jonathon Shlens, Alexander Toshev
On Robustness in Multimodal Learning. CoRR (2023)
Floris Weers, Vaishaal Shankar, Angelos Katharopoulos, Yinfei Yang, Tom Gunter
Self Supervision Does Not Help Natural Language Supervision at Scale. CoRR (2023)
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)
Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander Toshev, Vaishaal Shankar
Data Filtering Networks. CoRR (2023)
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)
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 (2022)
Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt
Predicting with Confidence on Unseen Distributions. CoRR (2021)
Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt
Do Image Classifiers Generalize Across Time? ICCV (2021)
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 (2021)
John P. 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)
Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt
Predicting with Confidence on Unseen Distributions. ICCV (2021)
Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt
Measuring Robustness to Natural Distribution Shifts in Image Classification. NeurIPS (2020)
Vaishaal Shankar, Rebecca Roelofs, Horia Mania, Alex Fang, Benjamin Recht, Ludwig Schmidt
Evaluating Machine Accuracy on ImageNet. ICML (2020)
Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Ludwig Schmidt, Jonathan Ragan-Kelley, Benjamin Recht
Neural Kernels Without Tangents. CoRR (2020)
Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht
Neural Kernels Without Tangents. ICML (2020)
Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran
Serverless Straggler Mitigation using Local Error-Correcting Codes. CoRR (2020)
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 (2020)
Vaishaal Shankar, Karl Krauth, Kailas Vodrahalli, Qifan Pu, Benjamin Recht, Ion Stoica, Jonathan Ragan-Kelley, Eric Jonas, Shivaram Venkataraman
Serverless linear algebra. SoCC (2020)
Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran
Serverless Straggler Mitigation using Error-Correcting Codes. ICDCS (2020)
Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt
Measuring Robustness to Natural Distribution Shifts in Image Classification. CoRR (2020)
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar
Do ImageNet Classifiers Generalize to ImageNet? ICML (2019)
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar
Do ImageNet Classifiers Generalize to ImageNet? CoRR (2019)
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 (2019)
Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt
A systematic framework for natural perturbations from videos. CoRR (2019)
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)
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar
Do CIFAR-10 Classifiers Generalize to CIFAR-10? CoRR (2018)
Vaishaal Shankar, Karl Krauth, Qifan Pu, Eric Jonas, Shivaram Venkataraman, Ion Stoica, Benjamin Recht, Jonathan Ragan-Kelley
numpywren: serverless linear algebra. CoRR (2018)
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 (2017)
Eric Jonas, Monica G. Bobra, Vaishaal Shankar, J. Todd Hoeksema, Benjamin Recht
Flare Prediction Using Photospheric and Coronal Image Data. CoRR (2017)
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)
Vaishaal Shankar, Jordan Zhang, Jerry Chen, Christopher Dinh, Matthew Clements, Avideh Zakhor
Approximate Subgraph Isomorphism for Image Localization. Image Processing: Algorithms and Systems (2016)
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 (2015)
Vaishaal Shankar, David E. Culler
A Modern Student Experience inSystems Programming. L@S (2015)
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)