Aditi Raghunathan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
38
Venues
9
Active years
2016–2025
Best venue rank
A*
Where they publish
Papers
38 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | Mitigating Bias in RAG: Controlling the Embedder. | Taeyoun Kim, Jacob Mitchell Springer, Aditi Raghunathan, Maarten Sap |
| 2025 | ACL | Understanding the Influence of Synthetic Data for Text Embedders. | Jacob Mitchell Springer, Vaibhav Adlakha, Siva Reddy, Aditi Raghunathan, Marius Mosbach |
| 2025 | AISTATS | Theory of Agreement-on-the-Line in Linear Models and Gaussian Data. | Christina Baek, Aditi Raghunathan, J. Zico Kolter |
| 2025 | EMNLP | Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions. | Emmy Liu, Amanda Bertsch, Lintang Sutawika, Lindia Tjuatja, Patrick Fernandes, Lara Marinov, Michael Chen, Shreya Singhal, Carolin Lawrence, Aditi Raghunathan, Kiril Gashteovski, Graham Neubig |
| 2025 | ICLR | Context-Parametric Inversion: Why Instruction Finetuning May Not Actually Improve Context Reliance. | Sachin Goyal, Christina Baek, J. Zico Kolter, Aditi Raghunathan |
| 2025 | ICLR | Scaling Laws for Precision. | Tanishq Kumar, Zachary Ankner, Benjamin Frederick Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher R, Aditi Raghunathan |
| 2025 | ICLR | Repetition Improves Language Model Embeddings. | Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, Graham Neubig, Aditi Raghunathan |
| 2025 | ICLR | Dissecting Adversarial Robustness of Multimodal LM Agents. | Chen Henry Wu, Rishi Rajesh Shah, Jing Yu Koh, Russ Salakhutdinov, Daniel Fried, Aditi Raghunathan |
| 2025 | ICML | Memorization Sinks: Isolating Memorization during LLM Training. | Gaurav Rohit Ghosal, Pratyush Maini, Aditi Raghunathan |
| 2025 | ICML | Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction. | Vaishnavh Nagarajan, Chen Henry Wu, Charles Ding, Aditi Raghunathan |
| 2025 | ICML | Overtrained Language Models Are Harder to Fine-Tune. | Jacob Mitchell Springer, Sachin Goyal, Kaiyue Wen, Tanishq Kumar, Xiang Yue, Sadhika Malladi, Graham Neubig, Aditi Raghunathan |
| 2025 | NAACL | On the Feasibility of In-Context Probing for Data Attribution. | Cathy Jiao, Weizhen Gao, Aditi Raghunathan, Chenyan Xiong |
| 2024 | CVPR | Scaling Laws for Data Filtering - Data Curation Cannot be Compute Agnostic. | Sachin Goyal, Pratyush Maini, Zachary C. Lipton, Aditi Raghunathan, J. Zico Kolter |
| 2024 | ICLR | Why is SAM Robust to Label Noise? | Christina Baek, J. Zico Kolter, Aditi Raghunathan |
| 2024 | ICLR | Understanding Catastrophic Forgetting in Language Models via Implicit Inference. | Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan |
| 2024 | ICLR | T-MARS: Improving Visual Representations by Circumventing Text Feature Learning. | Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J. Zico Kolter, Aditi Raghunathan |
| 2024 | ICLR | Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning. | Jacob Mitchell Springer, Vaishnavh Nagarajan, Aditi Raghunathan |
| 2024 | ICML | Understanding Finetuning for Factual Knowledge Extraction. | Gaurav Rohit Ghosal, Tatsunori Hashimoto, Aditi Raghunathan |
| 2023 | CVPR | Finetune like you pretrain: Improved finetuning of zero-shot vision models. | Sachin Goyal, Ananya Kumar, Sankalp Garg, Zico Kolter, Aditi Raghunathan |
| 2023 | ICLR | Using Language to Extend to Unseen Domains. | Lisa Dunlap, Clara Mohri, Devin Guillory, Han Zhang, Trevor Darrell, Joseph E. Gonzalez, Aditi Raghunathan, Anna Rohrbach |
| 2023 | ICLR | Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. | Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine |
| 2023 | ICML | Contextual Reliability: When Different Features Matter in Different Contexts. | Gaurav Rohit Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan |
| 2023 | ICML | Automatically Auditing Large Language Models via Discrete Optimization. | Erik Jones, Anca D. Dragan, Aditi Raghunathan, Jacob Steinhardt |
| 2022 | CoRL | Learning Representations that Enable Generalization in Assistive Tasks. | Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Aditi Raghunathan, Anca D. Dragan |
| 2022 | ICLR | Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution. | Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones, Tengyu Ma, Percy Liang |
| 2022 | ICLR | An Explanation of In-context Learning as Implicit Bayesian Inference. | Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma |
| 2022 | UAI | Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift. | Ananya Kumar, Tengyu Ma, Percy Liang, Aditi Raghunathan |
| 2021 | ICML | Just Train Twice: Improving Group Robustness without Training Group Information. | Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn |
| 2021 | ICML | Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices. | Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn |
| 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 | ACL | Robust Encodings: A Framework for Combating Adversarial Typos. | Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang |
| 2020 | ICML | DROCC: Deep Robust One-Class Classification. | Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain |
| 2020 | ICML | Understanding and Mitigating the Tradeoff between Robustness and Accuracy. | Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang |
| 2020 | ICML | An Investigation of Why Overparameterization Exacerbates Spurious Correlations. | Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang |
| 2019 | EMNLP | Certified Robustness to Adversarial Word Substitutions. | Robin Jia, Aditi Raghunathan, Kerem Gksel, Percy Liang |
| 2018 | ICLR | Certified Defenses against Adversarial Examples. | Aditi Raghunathan, Jacob Steinhardt, Percy Liang |
| 2017 | ICML | Estimating the unseen from multiple populations. | Aditi Raghunathan, Gregory Valiant, James Zou |
| 2016 | ICML | Estimation from Indirect Supervision with Linear Moments. | Aditi Raghunathan, Roy Frostig, John C. Duchi, Percy Liang |