Saurabh Garg

56 papers A* 21B 2Journal 28Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
An Artificial Intelligence Framework for Measuring Human Spine Aging Using MRI.
CoRR
Roozbeh Bazargani, Saqib Abdullah Basar, Daniel Daly-Grafstein, Rodrigo Solis Pompa, Soojin Lee, Saurabh Garg, Yuntong Ma, John A. Carrino, Siavash Khallaghi, Sam Hashemi
2025 J jnl
Expert Routing with Synthetic Data for Domain Incremental Learning.
Trans. Mach. Learn. Res.
Yewon Byun, Sanket Vaibhav Mehta, Saurabh Garg, Emma Strubell, Michael Oberst, Bryan Wilder, Zachary Chase Lipton
2024 A* conf
DataComp-LM: In search of the next generation of training sets for language models.
NeurIPS
Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
2024 J jnl
DataComp-LM: In search of the next generation of training sets for language models.
CoRR
Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
2024 J jnl
Generate to Discriminate: Expert Routing for Continual Learning.
CoRR
Yewon Byun, Sanket Vaibhav Mehta, Saurabh Garg, Emma Strubell, Michael Oberst, Bryan Wilder, Zachary C. Lipton
2024 A* conf
Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?
EMNLP
Daniel P. Jeong, Saurabh Garg, Zachary C. Lipton, Michael Oberst
2024 J jnl
Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?
CoRR
Daniel P. Jeong, Saurabh Garg, Zachary C. Lipton, Michael Oberst
2024 J jnl
Pixtral 12B.
CoRR
Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna, Baptiste Bout, Devendra Singh Chaplot, Jessica Chudnovsky, Diogo Costa, Baudouin De Monicault, Saurabh Garg, Théophile Gervet, Soham Ghosh, Amélie Héliou, Paul Jacob, Albert Q. Jiang, Kartik Khandelwal, Timothée Lacroix, Guillaume Lample, Diego de Las Casas, Thibaut Lavril, Teven Le Scao, Andy Lo, William Marshall, Louis Martin, Arthur Mensch, Pavankumar Muddireddy, Valera Nemychnikova, Marie Pellat, Patrick von Platen, Nikhil Raghuraman, Baptiste Rozière, Alexandre Sablayrolles, Lucile Saulnier, Romain Sauvestre, Wendy Shang, Roman Soletskyi, Lawrence Stewart, Pierre Stock, Joachim Studnia, Sandeep Subramanian, Sagar Vaze, Thomas Wang, Sophia Yang
2024 A* conf
Post-Hoc Reversal: Are We Selecting Models Prematurely?
NeurIPS
Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary C. Lipton
2024 J jnl
Post-Hoc Reversal: Are We Selecting Models Prematurely?
CoRR
Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary Chase Lipton
2024 A* conf
Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models.
ICML
Amrith Setlur, Saurabh Garg, Virginia Smith, Sergey Levine
2024 A* conf
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold.
NeurIPS
Amrith Setlur, Saurabh Garg, Xinyang Geng, Naman Garg, Virginia Smith, Aviral Kumar
2024 J jnl
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold.
CoRR
Amrith Setlur, Saurabh Garg, Xinyang Geng, Naman Garg, Virginia Smith, Aviral Kumar
2024 — —
Robust Machine Learning: Detection, Evaluation and Adaptation Under Distribution Shift
Saurabh Garg
2024 J jnl
The Limited Impact of Medical Adaptation of Large Language and Vision-Language Models.
CoRR
Daniel P. Jeong, Pranav Mani, Saurabh Garg, Zachary C. Lipton, Michael Oberst
2024 A* conf
TiC-CLIP: Continual Training of CLIP Models.
ICLR
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri
2023 A* conf
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy.
NeurIPS
Elan Rosenfeld, Saurabh Garg
2023 J jnl
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy.
CoRR
Elan Rosenfeld, Saurabh Garg
2023 A* conf
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets.
ICML
Zachary Novack, Julian J. McAuley, Zachary Chase Lipton, Saurabh Garg
2023 J jnl
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets.
CoRR
Zachary Novack, Saurabh Garg, Julian J. McAuley, Zachary C. Lipton
2023 A* conf
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.
NeurIPS
Saurabh Garg, Amrith Setlur, Zachary C. Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan
2023 J jnl
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.
CoRR
Saurabh Garg, Amrith Setlur, Zachary Chase Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan
2023 A* conf
Deconstructing Distributions: A Pointwise Framework of Learning.
ICLR
Gal Kaplun, Nikhil Ghosh, Saurabh Garg, Boaz Barak, Preetum Nakkiran
2023 A* conf
Disentangling the Mechanisms Behind Implicit Regularization in SGD.
ICLR
Zachary Novack, Simran Kaur, Tanya Marwah, Saurabh Garg, Zachary Chase Lipton
2023 — conf
Downstream Datasets Make Surprisingly Good Pretraining Corpora.
ACL (1)
Kundan Krishna, Saurabh Garg, Jeffrey P. Bigham, Zachary C. Lipton
2023 A* conf
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms.
NeurIPS
Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary C. Lipton, Yu-Xiang Wang
2023 J jnl
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms.
CoRR
Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary Chase Lipton, Yu-Xiang Wang
2023 A* conf
RLSbench: Domain Adaptation Under Relaxed Label Shift.
ICML
Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton
2023 J jnl
RLSbench: Domain Adaptation Under Relaxed Label Shift.
CoRR
Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary C. Lipton
2023 J jnl
TiC-CLIP: Continual Training of CLIP Models.
CoRR
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri
2022 A* conf
Characterizing Datapoints via Second-Split Forgetting.
NeurIPS
Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter
2022 J jnl
Characterizing Datapoints via Second-Split Forgetting.
CoRR
Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter
2022 J jnl
Deconstructing Distributions: A Pointwise Framework of Learning.
CoRR
Gal Kaplun, Nikhil Ghosh, Saurabh Garg, Boaz Barak, Preetum Nakkiran
2022 J jnl
Disentangling the Mechanisms Behind Implicit Regularization in SGD.
CoRR
Zachary Novack, Simran Kaur, Tanya Marwah, Saurabh Garg, Zachary C. Lipton
2022 A* conf
Domain Adaptation under Open Set Label Shift.
NeurIPS
Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton
2022 J jnl
Domain Adaptation under Open Set Label Shift.
CoRR
Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton
2022 J jnl
Downstream Datasets Make Surprisingly Good Pretraining Corpora.
CoRR
Kundan Krishna, Saurabh Garg, Jeffrey P. Bigham, Zachary C. Lipton
2022 J jnl
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance.
CoRR
Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton, Behnam Neyshabur, Hanie Sedghi
2022 A* conf
Leveraging unlabeled data to predict out-of-distribution performance.
ICLR
Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi
2022 A* conf
Unsupervised Learning under Latent Label Shift.
NeurIPS
Manley Roberts, Pranav Mani, Saurabh Garg, Zachary C. Lipton
2022 J jnl
Unsupervised Learning under Latent Label Shift.
CoRR
Manley Roberts, Pranav Mani, Saurabh Garg, Zachary C. Lipton
2021 — conf
Comparison of Touch and Touchless Zoom Control Methods for Single-Handed Mobile Interaction.
AHFE (7)
Saurabh Garg, I. Scott MacKenzie
2021 — conf
Fingerprint Scroll: Comparison of Touchless and Touch-Based Scroll Navigation Methods.
INTERACT (3)
Saurabh Garg, I. Scott MacKenzie
2021 A* conf
Mixture Proportion Estimation and PU Learning: A Modern Approach.
NeurIPS
Saurabh Garg, Yifan Wu, Alexander J. Smola, Sivaraman Balakrishnan, Zachary C. Lipton
2021 J jnl
Mixture Proportion Estimation and PU Learning: A Modern Approach.
CoRR
Saurabh Garg, Yifan Wu, Alex Smola, Sivaraman Balakrishnan, Zachary C. Lipton
2021 A* conf
On Proximal Policy Optimization's Heavy-tailed Gradients.
ICML
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Zachary C. Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar
2021 J jnl
On Proximal Policy Optimization's Heavy-tailed Gradients.
CoRR
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Sivaraman Balakrishnan, Zachary C. Lipton, Ruslan Salakhutdinov, Pradeep Ravikumar
2021 A* conf
RATT: Leveraging Unlabeled Data to Guarantee Generalization.
ICML
Saurabh Garg, Sivaraman Balakrishnan, J. Zico Kolter, Zachary C. Lipton
2021 J jnl
RATT: Leveraging Unlabeled Data to Guarantee Generalization.
CoRR
Saurabh Garg, Sivaraman Balakrishnan, J. Zico Kolter, Zachary C. Lipton
2020 A* conf
A Unified View of Label Shift Estimation.
NeurIPS
Saurabh Garg, Yifan Wu, Sivaraman Balakrishnan, Zachary C. Lipton
2020 J jnl
A Unified View of Label Shift Estimation.
CoRR
Saurabh Garg, Yifan Wu, Sivaraman Balakrishnan, Zachary C. Lipton
2015 — conf
A testbed for SCADA cyber security and intrusion detection.
SSIC
Prateek Singh, Saurabh Garg, Vinod Kumar, Zia Saquib
2004 J jnl
AGenDA: gene prediction by cross-species sequence comparison.
Nucleic Acids Res.
Leila Taher, Oliver Rinner, Saurabh Garg, Alexander Sczyrba, Burkhard Morgenstern
2004 B conf
Evaluation of Transcription and Annotation Tools for a Multi-modal, Multi-party Dialogue Corpus.
LREC
Saurabh Garg, Bilyana Martinovski, Susan Robinson, Jens Stephan, Joel R. Tetreault, David R. Traum
2004 B conf
Issues in Corpus Development for Multi-party Multi-modal Task-oriented Dialogue.
LREC
Susan Robinson, Bilyana Martinovski, Saurabh Garg, Jens Stephan, David R. Traum
2003 J jnl
AGenDA: homology-based gene prediction.
Bioinform.
Leila Taher, Oliver Rinner, Saurabh Garg, Alexander Sczyrba, Michael Brudno, Serafim Batzoglou, Burkhard Morgenstern