---
title: "Aditi Raghunathan — all works — Elamur Research"
description: "All 29 works of Aditi Raghunathan 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/aditi-raghunathan/works/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/aditi-raghunathan/works/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Aditi Raghunathan](https://md.research.elamur.ai/free/en/authors/aditi-raghunathan/) / all works

# Aditi Raghunathan — all works

29 works · [← Aditi Raghunathan](https://md.research.elamur.ai/free/en/authors/aditi-raghunathan/)

1. **[Certified Defenses against Adversarial Examples ↗](https://arxiv.org/abs/1801.09344) arXiv (Cornell University) · no summary yet**Aditi Raghunathan, Jacob Steinhardt, Percy Liang*2018 · 550 citations*
2. **[Certified Robustness to Adversarial Word Substitutions](https://md.research.elamur.ai/free/en/papers/jia-2019-certified-robustness-adversarial-word-substitutions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Robin Jia, Aditi Raghunathan, Kerem Göksel, et al.*2019 · 340 citations*
3. [**An Explanation of In-context Learning as Implicit Bayesian Inference arXiv:2111.02080**Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.*2021 · 286 citations*](https://md.research.elamur.ai/free/en/papers/xie-2021-explanation-context-learning-implicit-bayesian/)
4. **[Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution ↗](https://arxiv.org/abs/2202.10054) arXiv (Cornell University) · no summary yet**Ananya Kumar et al.*2022 · 248 citations*
5. **[Semidefinite relaxations for certifying robustness to adversarial examples ↗](https://arxiv.org/abs/1811.01057) arXiv (Cornell University) · no summary yet**Aditi Raghunathan, Jacob Steinhardt, Percy Liang*2018 · 201 citations*
6. **[An Investigation of Why Overparameterization Exacerbates Spurious Correlations ↗](https://arxiv.org/abs/2005.04345) arXiv (Cornell University) · no summary yet**Shiori Sagawa et al.*2020 · 147 citations*
7. **[Adversarial Training Can Hurt Generalization ↗](https://arxiv.org/abs/1906.06032) arXiv (Cornell University) · no summary yet**Aditi Raghunathan et al.*2019 · 139 citations*
8. **[Robust Encodings: A Framework for Combating Adversarial Typos ↗](https://aclanthology.org/2020.acl-main.245/) Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yet**Erik Jones et al.*2020 · 126 citations*
9. **[Just Train Twice: Improving Group Robustness without Training Group Information ↗](https://arxiv.org/abs/2107.09044) arXiv (Cornell University) · no summary yet**Evan Zheran Liu et al.*2021 · 125 citations*
10. **[Unlabeled Data Improves Adversarial Robustness ↗](https://arxiv.org/abs/1905.13736) arXiv (Cornell University) · no summary yet**Yair Carmon et al.*2019 · 91 citations*
11. [**Automatically Auditing Large Language Models via Discrete Optimization arXiv:2303.04381**Erik Jones, Anca Dragan, Aditi Raghunathan, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/jones-2023-automatically-auditing-large-language-models/)
12. [**Repetition Improves Language Model Embeddings arXiv:2402.15449**Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/)
13. **[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*
14. **[Understanding and Mitigating the Tradeoff Between Robustness and Accuracy ↗](https://arxiv.org/abs/2002.10716) arXiv (Cornell University) · no summary yet**Aditi Raghunathan et al.*2020 · 58 citations*
15. [**Understanding Catastrophic Forgetting in Language Models via Implicit Inference arXiv:2309.10105**Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/kotha-2023-understanding-catastrophic-forgetting-language-models/)
16. **[Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming ↗](https://arxiv.org/abs/2010.11645) arXiv:2010.11645 · no summary yet**Sumanth Dathathri et al.*2020 · 21 citations*
17. **[Dissecting Adversarial Robustness of Multimodal LM Agents ↗](https://arxiv.org/abs/2406.12814) arXiv (Cornell University) · no summary yet**Chen Henry Wu et al.*2024 · 20 citations*
18. **[Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices ↗](https://arxiv.org/abs/2008.02790) arXiv (Cornell University) · no summary yet**Evan Zheran Liu et al.*2020 · 14 citations*
19. **[Maximum Weighted Loss Discrepancy ↗](https://arxiv.org/abs/1906.03518) arXiv (Cornell University) · no summary yet**Fereshte Khani, Aditi Raghunathan, Percy Liang*2019 · 11 citations*
20. **[Weight Ensembling Improves Reasoning in Language Models ↗](https://arxiv.org/abs/2504.10478) arXiv:2504.10478 · COLM 2025 · no summary yet**Xingyu Dang et al.*2025 · 10 citations*
21. **[Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift ↗](https://arxiv.org/abs/2207.08977) arXiv (Cornell University) · no summary yet**Ananya Kumar et al.*2022 · 10 citations*
22. **[Estimation from Indirect Supervision with Linear Moments ↗](https://arxiv.org/abs/1608.03100) arXiv (Cornell University) · no summary yet**Aditi Raghunathan et al.*2016 · 9 citations*
23. **[Overtrained Language Models Are Harder to Fine-Tune ↗](https://arxiv.org/abs/2503.19206) arXiv (Cornell University) · no summary yet**Jacob M. Springer et al.*2025 · 8 citations*
24. **[Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions ↗](https://aclanthology.org/2025.emnlp-main.830/) Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing · no summary yet**Emmy Liu et al.*2025 · 6 citations*
25. **[Using Language to Extend to Unseen Domains ↗](https://arxiv.org/abs/2210.09520) arXiv (Cornell University) · no summary yet**Lisa Dunlap et al.*2022 · 6 citations*
26. **[Multitask Learning Can Improve Worst-Group Outcomes ↗](https://arxiv.org/abs/2312.03151) arXiv (Cornell University) · no summary yet**Atharva Kulkarni et al.*2023 · 1 citation*
27. **[When Covariate-shifted Data Augmentation Increases Test Error And How to Fix It ↗](https://openalex.org/W3005161396) no summary yet**Sang Michael Xie et al.*2019 · 1 citation*
28. **[Overparameterization hurts worst-group accuracy with spurious correlations ↗](https://openalex.org/W3035466577) International Conference on Machine Learning · no summary yet**Shiori Sagawa et al.*2020*
29. **[Task-Agnostic Robust Encodings for Combating Adversarial Typos ↗](https://openalex.org/W2986649174) no summary yet**Erik Jones et al.*2019*