| 2024 | EMNLP | Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress? | Daniel P. Jeong, Saurabh Garg, Zachary C. Lipton, Michael Oberst |
| 2024 | ICLR | TiC-CLIP: Continual Training of CLIP Models. | Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri |
| 2024 | ICML | Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models. | Amrith Setlur, Saurabh Garg, Virginia Smith, Sergey Levine |
| 2023 | ACL | Downstream Datasets Make Surprisingly Good Pretraining Corpora. | Kundan Krishna, Saurabh Garg, Jeffrey P. Bigham, Zachary C. Lipton |
| 2023 | ICLR | Deconstructing Distributions: A Pointwise Framework of Learning. | Gal Kaplun, Nikhil Ghosh, Saurabh Garg, Boaz Barak, Preetum Nakkiran |
| 2023 | ICLR | Disentangling the Mechanisms Behind Implicit Regularization in SGD. | Zachary Novack, Simran Kaur, Tanya Marwah, Saurabh Garg, Zachary Chase Lipton |
| 2023 | ICML | RLSbench: Domain Adaptation Under Relaxed Label Shift. | Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton |
| 2023 | ICML | CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets. | Zachary Novack, Julian J. McAuley, Zachary Chase Lipton, Saurabh Garg |
| 2022 | ICLR | Leveraging unlabeled data to predict out-of-distribution performance. | Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi |
| 2021 | ICML | RATT: Leveraging Unlabeled Data to Guarantee Generalization. | Saurabh Garg, Sivaraman Balakrishnan, J. Zico Kolter, Zachary C. Lipton |
| 2021 | ICML | On Proximal Policy Optimization's Heavy-tailed Gradients. | Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Zachary C. Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar |
| 2021 | Interact | Fingerprint Scroll: Comparison of Touchless and Touch-Based Scroll Navigation Methods. | Saurabh Garg, I. Scott MacKenzie |
| 2019 | MICCAI | Functional Data and Long Short-Term Memory Networks for Diagnosis of Parkinson's Disease. | Saurabh Garg, Martin J. McKeown |
| 2018 | EMNLP | Code-switched Language Models Using Dual RNNs and Same-Source Pretraining. | Saurabh Garg, Tanmay Parekh, Preethi Jyothi |
| 2018 | ICASSP | Joint Gender-, Tone-, Vowel- Classification Via Novel Hierarchical Classification for Annotation of Monosyllabic Mandarin Word Tokens. | Saurabh Garg, Ghassan Hamarneh, Allard Jongman, Joan A. Sereno, Yue Wang |
| 2018 | Interspeech | Dual Language Models for Code Switched Speech Recognition. | Saurabh Garg, Tanmay Parekh, Preethi Jyothi |
| 2018 | MICCAI | Perfect MCMC Sampling in Bayesian MRFs for Uncertainty Estimation in Segmentation. | Saurabh Garg, Suyash P. Awate |
| 2015 | ICIP | A sensitive and efficient method for measuring change in cortical thickness using fuzzy correspondence in Alzheimer's disease. | Saurabh Garg, Lisa Tang, Anthony Traboulsee, Roger C. Tam |
| 2006 | DAS | Script Identification from Indian Documents. | Gopal Datt Joshi, Saurabh Garg, Jayanthi Sivaswamy |
| 2004 | LREC | Evaluation of Transcription and Annotation Tools for a Multi-modal, Multi-party Dialogue Corpus. | Saurabh Garg, Bilyana Martinovski, Susan Robinson, Jens Stephan, Joel R. Tetreault, David R. Traum |
| 2004 | LREC | Issues in Corpus Development for Multi-party Multi-modal Task-oriented Dialogue. | Susan Robinson, Bilyana Martinovski, Saurabh Garg, Jens Stephan, David R. Traum |