---
title: "Ludwig Schmidt — all works — Elamur Research"
description: "All 27 works of Ludwig Schmidt in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/ludwig-schmidt/works/"
---
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# Ludwig Schmidt — all works

27 works · [← Ludwig Schmidt](https://md.research.elamur.ai/free/en/authors/ludwig-schmidt/)

1. [**Towards Deep Learning Models Resistant to Adversarial Attacks arXiv:1706.06083**Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, et al.*2017 · 1,874 citations*](https://md.research.elamur.ai/free/en/papers/madry-2017-towards-deep-learning-models-resistant/)
2. **[Objaverse: A Universe of Annotated 3D Objects ↗](https://doi.org/10.1109/cvpr52729.2023.01263) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Matt Deitke et al.*2023 · 800 citations*
3. **[Measuring and Narrowing the Compositionality Gap in Language Models ↗](https://aclanthology.org/2023.findings-emnlp.378/) Findings of the Association for Computational Linguistics: EMNLP 2023 · no summary yet**Ofir Press et al.*2023 · 776 citations*
4. **[Reproducible scaling laws for contrastive language-image learning](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-language/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 769 citations*
5. **[Robust fine-tuning of zero-shot models ↗](https://doi.org/10.1109/cvpr52688.2022.00780) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Mitchell Wortsman et al.*2022 · 519 citations*
6. [**Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time arXiv:2203.05482**Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.*2022 · 507 citations*](https://md.research.elamur.ai/free/en/papers/wortsman-2022-model-soups-averaging-weights-multiple/)
7. [**Editing Models with Task Arithmetic arXiv:2212.04089**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
8. **[Measuring Robustness to Natural Distribution Shifts in Image Classification ↗](https://openalex.org/W3104911444) neural information processing systems · no summary yet**Rohan Taori et al.*2020 · 209 citations*
9. **[CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation ↗](https://doi.org/10.1109/cvpr52729.2023.02219) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Samir Yitzhak Gadre et al.*2023 · 193 citations*
10. **[Are aligned neural networks adversarially aligned?](https://md.research.elamur.ai/free/en/papers/carlini-2023-aligned-neural-networks-adversarially-aligned/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.*2023 · 157 citations*
11. **[Unlabeled Data Improves Adversarial Robustness ↗](https://arxiv.org/abs/1905.13736) arXiv (Cornell University) · no summary yet**Yair Carmon et al.*2019 · 91 citations*
12. **[Predicting with Confidence on Unseen Distributions ↗](https://doi.org/10.1109/iccv48922.2021.00117) IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yet**Devin Guillory et al.*2021 · 85 citations*
13. **[Data Filtering Networks ↗](https://arxiv.org/abs/2309.17425) arXiv:2309.17425 · no summary yet**Alex Fang et al.*2023 · 60 citations*
14. **[Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization ↗](https://arxiv.org/abs/2107.04649) arXiv (Cornell University) · no summary yet**John J. Miller et al.*2021 · 59 citations*
15. **[Improving Multimodal Datasets with Image Captioning ↗](https://arxiv.org/abs/2307.10350) arXiv:2307.10350 · no summary yet**Thao Nguyen et al.*2023 · 51 citations*
16. **[Stable and low-precision training for large-scale vision-language models ↗](https://arxiv.org/abs/2304.13013) arXiv:2304.13013 · no summary yet**Mitchell Wortsman et al.*2023 · 46 citations*
17. **[SWE-smith: Scaling Data for Software Engineering Agents ↗](https://doi.org/10.52202/085713-3239) neural information processing systems · no summary yet**John Yang et al.*2025 · 44 citations*
18. **[Resolving Discrepancies in Compute-Optimal Scaling of Language Models](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 19 citations*
19. **[Multilingual Diversity Improves Vision-Language Representations ↗](https://doi.org/10.52202/079017-2902) neural information processing systems · no summary yet**Thao Nguyen et al.*2024 · 16 citations*
20. **[Recycling the Web: A Method to Enhance Pre-training Data Quality and Quantity for Language Models ↗](https://arxiv.org/abs/2506.04689) arXiv (Cornell University) · no summary yet**Nguyen, Thao et al.*2025 · 11 citations*
21. **[Better Alignment with Instruction Back-and-Forth Translation ↗](https://aclanthology.org/2024.findings-emnlp.777/) Findings of the Association for Computational Linguistics: EMNLP 2024 · no summary yet**Thao Nguyen et al.*2024 · 10 citations*
22. **[Humans are Missing from AI Coding Agent Research ↗](https://arxiv.org/abs/2608.12355) arXiv (Cornell University) · no summary yet**Zora Z. Wang et al.*2026 · 6 citations*
23. **[NitroGen: An Open Foundation Model for Generalist Gaming Agents ↗](https://arxiv.org/abs/2601.02427) arXiv (Cornell University) · no summary yet**Loïc Magne et al.*2026 · 5 citations*
24. **[CodeClash: Benchmarking Goal-Oriented Software Engineering ↗](https://arxiv.org/abs/2511.00839) arXiv (Cornell University) · no summary yet**John Jeongseok Yang et al.*2025 · 3 citations*
25. **[Prefix Sliding for efficient test-time scaling ↗](https://arxiv.org/abs/2608.26070) arXiv (Cornell University) · no summary yet**Niklas Muennighoff et al.*2026 · 1 citation*
26. **[Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pre-training ↗](https://aclanthology.org/2026.findings-eacl.307/) Findings of the Association for Computational Linguistics: EACL 2026 · no summary yet**Jeffrey Li et al.*2026*
27. **[Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pretraining ↗](https://arxiv.org/abs/2602.19548) arXiv (Cornell University) · no summary yet**Jeffrey Li et al.*2026*