Ludwig Schmidt
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
45
Venues
15
Active years
2014–2026
Best venue rank
A*
Where they publish
Papers
45 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EACL | Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pre-training. | Jeffrey Li, Joshua P. Gardner, Doug Kang, Fangping Shi, Karanjeet Singh, Chun-Liang Li, Herumb Shandilya, David Leo Wright Hall, Oncel Tuzel, Percy Liang, Ludwig Schmidt, Hadi Pouransari, Fartash Faghri |
| 2025 | CVPR | Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation. | 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 |
| 2025 | EMNLP | Data or Language Supervision: What Makes CLIP Better than DINO? | Yiming Liu, Yuhui Zhang, Dhruba Ghosh, Ludwig Schmidt, Serena Yeung-Levy |
| 2025 | ICCV | BLIP-3: A Family of Open Large Multimodal Models. | 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, Shao-Yen Tseng, Gustavo A. Lujan-Moreno, Matthew L. Olson, Musashi Hinck, David Cobbley, Vasudev Lal, 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 |
| 2025 | ICLR | Should VLMs be Pre-trained with Image Data? | Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre, Kushal Arora, Igor Vasiljevic, Benjamin Burchfiel, Shuran Song, Russ Tedrake, Thomas Kollar, Ludwig Schmidt, Achal Dave |
| 2024 | ECCV | Getting it Right: Improving Spatial Consistency in Text-to-Image Models. | Agneet Chatterjee, Gabriela Ben Melech Stan, Estelle Aflalo, Sayak Paul, Dhruba Ghosh, Tejas Gokhale, Ludwig Schmidt, Hannaneh Hajishirzi, Vasudev Lal, Chitta Baral, Yezhou Yang |
| 2024 | EMNLP | Better Alignment with Instruction Back-and-Forth Translation. | Thao Nguyen, Jeffrey Li, Sewoong Oh, Ludwig Schmidt, Jason Weston, Luke Zettlemoyer, Xian Li |
| 2024 | ICLR | Data Filtering Networks. | Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T. Toshev, Vaishaal Shankar |
| 2023 | CVPR | Reproducible Scaling Laws for Contrastive Language-Image Learning. | Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev |
| 2023 | CVPR | Objaverse: A Universe of Annotated 3D Objects. | Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, Ali Farhadi |
| 2023 | CVPR | CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation. | Samir Yitzhak Gadre, Mitchell Wortsman, Gabriel Ilharco, Ludwig Schmidt, Shuran Song |
| 2023 | EMNLP | Measuring and Narrowing the Compositionality Gap in Language Models. | Ofir Press, Muru Zhang, Sewon Min, Ludwig Schmidt, Noah A. Smith, Mike Lewis |
| 2023 | ICCV | Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. | Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz |
| 2023 | ICLR | Editing models with task arithmetic. | Gabriel Ilharco, Marco Tlio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, Ali Farhadi |
| 2022 | CVPR | Robust fine-tuning of zero-shot models. | Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, Ludwig Schmidt |
| 2022 | EMNLP | Exploring The Landscape of Distributional Robustness for Question Answering Models. | Anas Awadalla, Mitchell Wortsman, Gabriel Ilharco, Sewon Min, Ian Magnusson, Hannaneh Hajishirzi, Ludwig Schmidt |
| 2022 | ICML | Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP). | Alex Fang, Gabriel Ilharco, Mitchell Wortsman, Yuhao Wan, Vaishaal Shankar, Achal Dave, Ludwig Schmidt |
| 2022 | ICML | Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. | 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 |
| 2021 | ICCV | Predicting with Confidence on Unseen Distributions. | Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt |
| 2021 | ICCV | Contrasting Contrastive Self-Supervised Representation Learning Pipelines. | Klemen Kotar, Gabriel Ilharco, Ludwig Schmidt, Kiana Ehsani, Roozbeh Mottaghi |
| 2021 | ICCV | Do Image Classifiers Generalize Across Time? | Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt |
| 2021 | ICML | Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. | John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt |
| 2020 | ICML | The Effect of Natural Distribution Shift on Question Answering Models. | John Miller, Karl Krauth, Benjamin Recht, Ludwig Schmidt |
| 2020 | ICML | Neural Kernels Without Tangents. | Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht |
| 2020 | ICML | Evaluating Machine Accuracy on ImageNet. | Vaishaal Shankar, Rebecca Roelofs, Horia Mania, Alex Fang, Benjamin Recht, Ludwig Schmidt |
| 2019 | ICML | Exploring the Landscape of Spatial Robustness. | Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry |
| 2019 | ICML | Do ImageNet Classifiers Generalize to ImageNet? | Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, Vaishaal Shankar |
| 2018 | AISTATS | A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians. | Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt |
| 2018 | COLT | Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. | Ilias Diakonikolas, Jerry Li, Ludwig Schmidt |
| 2018 | ICLR | Towards Deep Learning Models Resistant to Adversarial Attacks. | Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu |
| 2018 | ICML | On the Limitations of First-Order Approximation in GAN Dynamics. | Jerry Li, Aleksander Madry, John Peebles, Ludwig Schmidt |
| 2018 | ICML | A Classification-Based Study of Covariate Shift in GAN Distributions. | Shibani Santurkar, Ludwig Schmidt, Aleksander Madry |
| 2017 | COLT | Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities. | Jerry Li, Ludwig Schmidt |
| 2017 | SODA | Sample-Optimal Density Estimation in Nearly-Linear Time. | Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt |
| 2017 | SODA | Better Approximations for Tree Sparsity in Nearly-Linear Time. | Arturs Backurs, Piotr Indyk, Ludwig Schmidt |
| 2016 | ICML | Fast Algorithms for Segmented Regression. | Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt |
| 2016 | IJCAI | A Nearly-Linear Time Framework for Graph-Structured Sparsity. | Chinmay Hegde, Piotr Indyk, Ludwig Schmidt |
| 2015 | ICASSP | Seismic feature extraction using steiner tree methods. | Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Ligang Lu, Xingang Chi, Detlef Hohl |
| 2015 | ICML | A Nearly-Linear Time Framework for Graph-Structured Sparsity. | Chinmay Hegde, Piotr Indyk, Ludwig Schmidt |
| 2015 | PODS | Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms. | Jayadev Acharya, Ilias Diakonikolas, Chinmay Hegde, Jerry Zheng Li, Ludwig Schmidt |
| 2014 | ICALP | Nearly Linear-Time Model-Based Compressive Sensing. | Chinmay Hegde, Piotr Indyk, Ludwig Schmidt |
| 2014 | ICASSP | Automatic fault localization using the generalized Earth Mover's distance. | Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Jonathan Kane, Ligang Lu, Detlef Hohl |
| 2014 | ICASSP | Large-scale speaker identification. | Ludwig Schmidt, Matthew Sharifi, Ignacio Lpez-Moreno |
| 2014 | ISIT | A fast approximation algorithm for tree-sparse recovery. | Chinmay Hegde, Piotr Indyk, Ludwig Schmidt |
| 2014 | SODA | Approximation-Tolerant Model-Based Compressive Sensing. | Chinmay Hegde, Piotr Indyk, Ludwig Schmidt |