default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLudwig Schmidt
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[c82]Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre, Kushal Arora, Igor Vasiljevic, Benjamin Burchfiel, Shuran Song, Russ Tedrake, Thomas Kollar, Ludwig Schmidt, Achal Dave:
Should VLMs be Pre-trained with Image Data? ICLR 2025- [i78]Yuhui Zhang, Yuchang Su, Yiming Liu, Xiaohan Wang, James Burgess, Elaine Sui, Chenyu Wang, Josiah Aklilu, Alejandro Lozano, Anjiang Wei, Ludwig Schmidt, Serena Yeung-Levy:
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation. CoRR abs/2501.03225 (2025) - [i77]Christoph Schuhmann, Gollam Rabby, Ameya Prabhu, Tawsif Ahmed, Andreas Hochlehnert, Huu Nguyen, Nick Akinci Heidrich, Ludwig Schmidt, Robert Kaczmarczyk, Sören Auer, Jenia Jitsev, Matthias Bethge:
Project Alexandria: Towards Freeing Scientific Knowledge from Copyright Burdens via LLMs. CoRR abs/2502.19413 (2025) - [i76]Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre, Kushal Arora, Igor Vasiljevic, Benjamin Burchfiel, Shuran Song, Russ Tedrake, Thomas Kollar, Ludwig Schmidt, Achal Dave:
Should VLMs be Pre-trained with Image Data? CoRR abs/2503.07603 (2025) - [i75]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) - [i74]John Yang, Kilian Leret, Carlos E. Jimenez, Alexander Wettig, Kabir Khandpur, Yanzhe Zhang, Binyuan Hui, Ofir Press, Ludwig Schmidt, Diyi Yang:
SWE-smith: Scaling Data for Software Engineering Agents. CoRR abs/2504.21798 (2025) - 2024
- [j6]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) - [c81]Agneet Chatterjee, Gabriela Ben Melech Stan, Estelle Aflalo, Sayak Paul, Dhruba Ghosh, Tejas Gokhale, Ludwig Schmidt, Hannaneh Hajishirzi, Vasudev Lal, Chitta Baral, Yezhou Yang:
Getting it Right: Improving Spatial Consistency in Text-to-Image Models. ECCV (22) 2024: 204-222 - [c80]Thao Nguyen, Jeffrey Li, Sewoong Oh, Ludwig Schmidt, Jason Weston, Luke Zettlemoyer, Xian Li:
Better Alignment with Instruction Back-and-Forth Translation. EMNLP (Findings) 2024: 13289-13308 - [c79]Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T. Toshev, Vaishaal Shankar:
Data Filtering Networks. ICLR 2024 - [c78]Josh Gardner, Juan C. Perdomo, Ludwig Schmidt:
Large Scale Transfer Learning for Tabular Data via Language Modeling. NeurIPS 2024 - [c77]Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Guha, Sheng Shen, Mohamed Awadalla, Silvio Savarese, Caiming Xiong, Ran Xu, Yejin Choi, Ludwig Schmidt:
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens. NeurIPS 2024 - [c76]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 - [c75]Thao Nguyen, Matthew Wallingford, Sebastin Santy, Wei-Chiu Ma, Sewoong Oh, Ludwig Schmidt, Pang Wei W. Koh, Ranjay Krishna:
Multilingual Diversity Improves Vision-Language Representations. NeurIPS 2024 - [c74]Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon:
Resolving Discrepancies in Compute-Optimal Scaling of Language Models. NeurIPS 2024 - [c73]Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang:
A Sober Look at the Robustness of CLIPs to Spurious Features. NeurIPS 2024 - [c72]Yuhui Zhang, Alyssa Unell, Xiaohan Wang, Dhruba Ghosh, Yuchang Su, Ludwig Schmidt, Serena Yeung:
Why are Visually-Grounded Language Models Bad at Image Classification? NeurIPS 2024 - [i73]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) - [i72]Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang:
Do CLIPs Always Generalize Better than ImageNet Models? CoRR abs/2403.11497 (2024) - [i71]Agneet Chatterjee, Gabriela Ben Melech Stan, Estelle Aflalo, Sayak Paul, Dhruba Ghosh, Tejas Gokhale, Ludwig Schmidt, Hannaneh Hajishirzi, Vasudev Lal, Chitta Baral, Yezhou Yang:
Getting it Right: Improving Spatial Consistency in Text-to-Image Models. CoRR abs/2404.01197 (2024) - [i70]Thao Nguyen, Matthew Wallingford, Sebastin Santy, Wei-Chiu Ma, Sewoong Oh, Ludwig Schmidt, Pang Wei Koh, Ranjay Krishna:
Multilingual Diversity Improves Vision-Language Representations. CoRR abs/2405.16915 (2024) - [i69]Yuhui Zhang, Alyssa Unell, Xiaohan Wang, Dhruba Ghosh, Yuchang Su, Ludwig Schmidt, Serena Yeung-Levy:
Why are Visually-Grounded Language Models Bad at Image Classification? CoRR abs/2405.18415 (2024) - [i68]Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Kumar Guha, Matt Jordan, Sheng Shen, Mohamed Awadalla, Silvio Savarese, Caiming Xiong, Ran Xu, Yejin Choi, Ludwig Schmidt:
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens. CoRR abs/2406.11271 (2024) - [i67]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) - [i66]Josh Gardner, Juan C. Perdomo, Ludwig Schmidt:
Large Scale Transfer Learning for Tabular Data via Language Modeling. CoRR abs/2406.12031 (2024) - [i65]Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon:
Resolving Discrepancies in Compute-Optimal Scaling of Language Models. CoRR abs/2406.19146 (2024) - [i64]Thao Nguyen, Jeffrey Li, Sewoong Oh, Ludwig Schmidt, Jason Weston, Luke Zettlemoyer, Xian Li:
Better Alignment with Instruction Back-and-Forth Translation. CoRR abs/2408.04614 (2024) - [i63]Le Xue, Manli Shu, Anas Awadalla, Jun Wang, An Yan, Senthil Purushwalkam, Honglu Zhou, Viraj Prabhu, Yutong Dai, Michael S. Ryoo, Shrikant Kendre, Jieyu Zhang, Can Qin, Shu Zhang, Chia-Chih Chen, Ning Yu, Juntao Tan, Tulika Manoj Awalgaonkar, Shelby Heinecke, Huan Wang, Yejin Choi, Ludwig Schmidt, Zeyuan Chen, Silvio Savarese, Juan Carlos Niebles, Caiming Xiong, Ran Xu:
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models. CoRR abs/2408.08872 (2024) - [i62]Anas Awadalla, Le Xue, Manli Shu, An Yan, Jun Wang, Senthil Purushwalkam, Sheng Shen, Hannah Lee, Oscar Lo, Jae Sung Park, Etash Guha, Silvio Savarese, Ludwig Schmidt, Yejin Choi, Caiming Xiong, Ran Xu:
BLIP3-KALE: Knowledge Augmented Large-Scale Dense Captions. CoRR abs/2411.07461 (2024) - 2023
- [j5]Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory W. Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu:
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. Trans. Mach. Learn. Res. 2023 (2023) - [j4]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) - [c71]Mike A. Merrill, Esteban Safranchik, Arinbjörn Kolbeinsson, Piyusha Gade, Ernesto Ramirez, Ludwig Schmidt, Luca Foshchini, Tim Althoff:
Homekit2020: A Benchmark for Time Series Classification on a Large Mobile Sensing Dataset with Laboratory Tested Ground Truth of Influenza Infections. CHIL 2023: 207-228 - [c70]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 - [c69]Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, Ali Farhadi:
Objaverse: A Universe of Annotated 3D Objects. CVPR 2023: 13142-13153 - [c68]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 - [c67]Ofir Press, Muru Zhang, Sewon Min, Ludwig Schmidt, Noah A. Smith, Mike Lewis:
Measuring and Narrowing the Compositionality Gap in Language Models. EMNLP (Findings) 2023: 5687-5711 - [c66]Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz:
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. ICCV 2023: 2616-2627 - [c65]Gabriel Ilharco, Marco Túlio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, Ali Farhadi:
Editing models with task arithmetic. ICLR 2023 - [c64]Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt:
VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models. NeurIPS 2023 - [c63]Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei Koh, Daphne Ippolito, Florian Tramèr, Ludwig Schmidt:
Are aligned neural networks adversarially aligned? NeurIPS 2023 - [c62]Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, Eli VanderBilt, Aniruddha Kembhavi, Carl Vondrick, Georgia Gkioxari, Kiana Ehsani, Ludwig Schmidt, Ali Farhadi:
Objaverse-XL: A Universe of 10M+ 3D Objects. NeurIPS 2023 - [c61]Alex Fang, Simon Kornblith, Ludwig Schmidt:
Does progress on ImageNet transfer to real-world datasets? NeurIPS 2023 - [c60]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 - [c59]Josh Gardner, Zoran Popovic, Ludwig Schmidt:
Benchmarking Distribution Shift in Tabular Data with TableShift. NeurIPS 2023 - [c58]Dhruba Ghosh, Hannaneh Hajishirzi, Ludwig Schmidt:
GenEval: An object-focused framework for evaluating text-to-image alignment. NeurIPS 2023 - [c57]Jeffrey Li, Jieyu Zhang, Ludwig Schmidt, Alexander J. Ratner:
Characterizing the Impacts of Semi-supervised Learning for Weak Supervision. NeurIPS 2023 - [c56]Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt:
Improving multimodal datasets with image captioning. NeurIPS 2023 - [c55]Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ali Farhadi, Ludwig Schmidt:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. NeurIPS 2023 - [c54]Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin:
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. NeurIPS 2023 - [c53]Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi:
Neural Priming for Sample-Efficient Adaptation. NeurIPS 2023 - [c52]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 - [c51]Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, Yejin Choi:
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text. NeurIPS 2023 - [i61]Alex Fang, Simon Kornblith, Ludwig Schmidt:
Does progress on ImageNet transfer to real-world datasets? CoRR abs/2301.04644 (2023) - [i60]Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin:
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. CoRR abs/2302.01381 (2023) - [i59]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) - [i58]Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz:
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. CoRR abs/2303.07274 (2023) - [i57]Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, Yejin Choi:
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved With Text. CoRR abs/2304.06939 (2023) - [i56]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) - [i55]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) - [i54]Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi:
Neural Priming for Sample-Efficient Adaptation. CoRR abs/2306.10191 (2023) - [i53]Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramèr, Ludwig Schmidt:
Are aligned neural networks adversarially aligned? CoRR abs/2306.15447 (2023) - [i52]Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, Eli VanderBilt, Aniruddha Kembhavi, Carl Vondrick, Georgia Gkioxari, Kiana Ehsani, Ludwig Schmidt, Ali Farhadi:
Objaverse-XL: A Universe of 10M+ 3D Objects. CoRR abs/2307.05663 (2023) - [i51]Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt:
Improving Multimodal Datasets with Image Captioning. CoRR abs/2307.10350 (2023) - [i50]Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ludwig Schmidt, Ali Farhadi:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. CoRR abs/2307.12532 (2023) - [i49]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) - [i48]Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt:
VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use. CoRR abs/2308.06595 (2023) - [i47]Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander Toshev, Vaishaal Shankar:
Data Filtering Networks. CoRR abs/2309.17425 (2023) - [i46]Dhruba Ghosh, Hanna Hajishirzi, Ludwig Schmidt:
GenEval: An Object-Focused Framework for Evaluating Text-to-Image Alignment. CoRR abs/2310.11513 (2023) - [i45]Josh Gardner, Zoran Popovic, Ludwig Schmidt:
Benchmarking Distribution Shift in Tabular Data with TableShift. CoRR abs/2312.07577 (2023) - 2022
- [c50]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 - [c49]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 - [c48]Rediet Abebe, Moritz Hardt, Angela Jin, John Miller, Ludwig Schmidt, Rebecca Wexler:
Adversarial Scrutiny of Evidentiary Statistical Software. FAccT 2022: 1733-1746 - [c47]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 - [c46]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 - [c45]Josh Gardner, Zoran Popovic, Ludwig Schmidt:
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation. NeurIPS 2022 - [c44]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 - [c43]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 - [c42]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 - [i44]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) - [i43]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) - [i42]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) - [i41]Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory W. Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu:
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. CoRR abs/2206.04615 (2022) - [i40]Rediet Abebe, Moritz Hardt, Angela Jin, John Miller, Ludwig Schmidt, Rebecca Wexler:
Adversarial Scrutiny of Evidentiary Statistical Software. CoRR abs/2206.09305 (2022) - [i39]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) - [i38]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) - [i37]Ofir Press, Muru Zhang, Sewon Min, Ludwig Schmidt, Noah A. Smith, Mike Lewis:
Measuring and Narrowing the Compositionality Gap in Language Models. CoRR abs/2210.03350 (2022) - [i36]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) - [i35]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) - [i34]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) - [i33]Josh Gardner, Zoran Popovic, Ludwig Schmidt:
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation. CoRR abs/2211.12703 (2022) - [i32]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) - [i31]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) - [i30]Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, Ali Farhadi:
Objaverse: A Universe of Annotated 3D Objects. CoRR abs/2212.08051 (2022) - 2021
- [c41]Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt:
Predicting with Confidence on Unseen Distributions. ICCV 2021: 1114-1124 - [c40]Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt:
Do Image Classifiers Generalize Across Time? ICCV 2021: 9641-9649 - [c39]Klemen Kotar, Gabriel Ilharco, Ludwig Schmidt, Kiana Ehsani, Roozbeh Mottaghi:
Contrasting Contrastive Self-Supervised Representation Learning Pipelines. ICCV 2021: 9929-9939 - [c38]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 - [c37]Frances Ding, Moritz Hardt, John Miller, Ludwig Schmidt:
Retiring Adult: New Datasets for Fair Machine Learning. NeurIPS 2021: 6478-6490 - [c36]Thomas Liao, Rohan Taori, Deborah Raji, Ludwig Schmidt:
Are We Learning Yet? A Meta Review of Evaluation Failures Across Machine Learning. NeurIPS Datasets and Benchmarks 2021 - [c35]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. NeurIPS 2021: 25006-25018 - [i29]Klemen Kotar, Gabriel Ilharco, Ludwig Schmidt, Kiana Ehsani, Roozbeh Mottaghi:
Contrasting Contrastive Self-Supervised Representation Learning Models. CoRR abs/2103.14005 (2021) - [i28]Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt:
Predicting with Confidence on Unseen Distributions. CoRR abs/2107.03315 (2021) - [i27]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) - [i26]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. CoRR abs/2107.09562 (2021) - [i25]Frances Ding, Moritz Hardt, John Miller, Ludwig Schmidt:
Retiring Adult: New Datasets for Fair Machine Learning. CoRR abs/2108.04884 (2021) - [i24]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
- [c34]John Miller, Karl Krauth, Benjamin Recht, Ludwig Schmidt:
The Effect of Natural Distribution Shift on Question Answering Models. ICML 2020: 6905-6916 - [c33]Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht:
Neural Kernels Without Tangents. ICML 2020: 8614-8623 - [c32]Vaishaal Shankar, Rebecca Roelofs, Horia Mania, Alex Fang, Benjamin Recht, Ludwig Schmidt:
Evaluating Machine Accuracy on ImageNet. ICML 2020: 8634-8644 - [c31]Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt:
Measuring Robustness to Natural Distribution Shifts in Image Classification. NeurIPS 2020 - [i23]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) - [i22]John Miller, Karl Krauth, Benjamin Recht, Ludwig Schmidt:
The Effect of Natural Distribution Shift on Question Answering Models. CoRR abs/2004.14444 (2020) - [i21]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)
2010 – 2019
- 2019
- [c30]Smitha Milli, Ludwig Schmidt, Anca D. Dragan, Moritz Hardt:
Model Reconstruction from Model Explanations. FAT 2019: 1-9 - [c29]Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry:
Exploring the Landscape of Spatial Robustness. ICML 2019: 1802-1811 - [c28]Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar:
Do ImageNet Classifiers Generalize to ImageNet? ICML 2019: 5389-5400 - [c27]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 - [c26]Horia Mania, John Miller, Ludwig Schmidt, Moritz Hardt, Benjamin Recht:
Model Similarity Mitigates Test Set Overuse. NeurIPS 2019: 9993-10002 - [c25]Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, John C. Duchi, Percy Liang:
Unlabeled Data Improves Adversarial Robustness. NeurIPS 2019: 11190-11201 - [i20]Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar:
Do ImageNet Classifiers Generalize to ImageNet? CoRR abs/1902.10811 (2019) - [i19]Horia Mania, John Miller, Ludwig Schmidt, Moritz Hardt, Benjamin Recht:
Model Similarity Mitigates Test Set Overuse. CoRR abs/1905.12580 (2019) - [i18]Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, Percy Liang, John C. Duchi:
Unlabeled Data Improves Adversarial Robustness. CoRR abs/1905.13736 (2019) - [i17]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
- [b1]Ludwig Schmidt:
Algorithms above the noise floor. Massachusetts Institute of Technology, Cambridge, USA, 2018 - [c24]Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt:
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians. AISTATS 2018: 20-28 - [c23]Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. COLT 2018: 819-842 - [c22]Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu:
Towards Deep Learning Models Resistant to Adversarial Attacks. ICLR (Poster) 2018 - [c21]Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt:
On the Limitations of First-Order Approximation in GAN Dynamics. ICML 2018: 3011-3019 - [c20]Shibani Santurkar, Ludwig Schmidt, Aleksander Madry:
A Classification-Based Study of Covariate Shift in GAN Distributions. ICML 2018: 4487-4496 - [c19]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. NeurIPS 2018: 5019-5031 - [i16]Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. CoRR abs/1802.08513 (2018) - [i15]Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Madry:
Adversarially Robust Generalization Requires More Data. CoRR abs/1804.11285 (2018) - [i14]Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar:
Do CIFAR-10 Classifiers Generalize to CIFAR-10? CoRR abs/1806.00451 (2018) - [i13]Smitha Milli, Ludwig Schmidt, Anca D. Dragan, Moritz Hardt:
Model Reconstruction from Model Explanations. CoRR abs/1807.05185 (2018) - 2017
- [c18]Jerry Li, Ludwig Schmidt:
Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities. COLT 2017: 1302-1382 - [c17]Arturs Backurs, Piotr Indyk, Ludwig Schmidt:
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks. NIPS 2017: 4308-4318 - [c16]Ilias Diakonikolas, Elena Grigorescu, Jerry Li, Abhiram Natarajan, Krzysztof Onak, Ludwig Schmidt:
Communication-Efficient Distributed Learning of Discrete Distributions. NIPS 2017: 6391-6401 - [c15]Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Sample-Optimal Density Estimation in Nearly-Linear Time. SODA 2017: 1278-1289 - [c14]Arturs Backurs, Piotr Indyk, Ludwig Schmidt:
Better Approximations for Tree Sparsity in Nearly-Linear Time. SODA 2017: 2215-2229 - [i12]Arturs Backurs, Piotr Indyk, Ludwig Schmidt:
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks. CoRR abs/1704.02958 (2017) - [i11]Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu:
Towards Deep Learning Models Resistant to Adversarial Attacks. CoRR abs/1706.06083 (2017) - [i10]Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt:
Towards Understanding the Dynamics of Generative Adversarial Networks. CoRR abs/1706.09884 (2017) - [i9]Shibani Santurkar, Ludwig Schmidt, Aleksander Madry:
A Classification-Based Perspective on GAN Distributions. CoRR abs/1711.00970 (2017) - [i8]Logan Engstrom, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry:
A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations. CoRR abs/1712.02779 (2017) - [i7]Alexander LeNail, Ludwig Schmidt, Johnathan Li, Tobias Ehrenberger, Karen Sachs, Stefanie Jegelka, Ernest Fraenkel:
Graph-Sparse Logistic Regression. CoRR abs/1712.05510 (2017) - [i6]Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt:
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians. CoRR abs/1712.08130 (2017) - 2016
- [c13]Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast Algorithms for Segmented Regression. ICML 2016: 2878-2886 - [c12]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
A Nearly-Linear Time Framework for Graph-Structured Sparsity. IJCAI 2016: 4165-4169 - [c11]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Fast recovery from a union of subspaces. NIPS 2016: 4394-4402 - [i5]Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt:
Fast Algorithms for Segmented Regression. CoRR abs/1607.03990 (2016) - 2015
- [j3]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Fast Algorithms for Structured Sparsity. Bull. EATCS 117 (2015) - [j2]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Approximation Algorithms for Model-Based Compressive Sensing. IEEE Trans. Inf. Theory 61(9): 5129-5147 (2015) - [c10]Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Ligang Lu, Xingang Chi, Detlef Hohl:
Seismic feature extraction using steiner tree methods. ICASSP 2015: 1647-1651 - [c9]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
A Nearly-Linear Time Framework for Graph-Structured Sparsity. ICML 2015: 928-937 - [c8]Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya P. Razenshteyn, Ludwig Schmidt:
Practical and Optimal LSH for Angular Distance. NIPS 2015: 1225-1233 - [c7]Ilias Diakonikolas, Moritz Hardt, Ludwig Schmidt:
Differentially Private Learning of Structured Discrete Distributions. NIPS 2015: 2566-2574 - [c6]Jayadev Acharya, Ilias Diakonikolas, Chinmay Hegde, Jerry Zheng Li, Ludwig Schmidt:
Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms. PODS 2015: 249-263 - [i4]Jayadev Acharya, Ilias Diakonikolas, Jerry Zheng Li, Ludwig Schmidt:
Sample-Optimal Density Estimation in Nearly-Linear Time. CoRR abs/1506.00671 (2015) - [i3]Jerry Zheng Li, Ludwig Schmidt:
A Nearly Optimal and Agnostic Algorithm for Properly Learning a Mixture of k Gaussians, for any Constant k. CoRR abs/1506.01367 (2015) - [i2]Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya P. Razenshteyn, Ludwig Schmidt:
Practical and Optimal LSH for Angular Distance. CoRR abs/1509.02897 (2015) - 2014
- [j1]Anna C. Gilbert, Piotr Indyk, Mark A. Iwen, Ludwig Schmidt:
Recent Developments in the Sparse Fourier Transform: A compressed Fourier transform for big data. IEEE Signal Process. Mag. 31(5): 91-100 (2014) - [c5]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Nearly Linear-Time Model-Based Compressive Sensing. ICALP (1) 2014: 588-599 - [c4]Ludwig Schmidt, Matthew Sharifi, Ignacio López-Moreno:
Large-scale speaker identification. ICASSP 2014: 1650-1654 - [c3]Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Jonathan Kane, Ligang Lu, Detlef Hohl:
Automatic fault localization using the generalized Earth Mover's distance. ICASSP 2014: 8134-8138 - [c2]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
A fast approximation algorithm for tree-sparse recovery. ISIT 2014: 1842-1846 - [c1]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Approximation-Tolerant Model-Based Compressive Sensing. SODA 2014: 1544-1561 - [i1]Chinmay Hegde, Piotr Indyk, Ludwig Schmidt:
Approximation Algorithms for Model-Based Compressive Sensing. CoRR abs/1406.1579 (2014)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-05-26 21:57 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
