Amrith Setlur

According to our database, Amrith Setlur authored at least 24 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Multitask Learning Can Improve Worst-Group Outcomes.

Atharva Kulkarni, Lucio M. Dery, Amrith Setlur, Aditi Raghunathan, Ameet Talwalkar, Graham Neubig

Trans. Mach. Learn. Res., 2024

Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning.

Amrith Setlur, Chirag Nagpal, Adam Fisch, Xinyang Geng, Jacob Eisenstein, Rishabh Agarwal, Alekh Agarwal, Jonathan Berant, Aviral Kumar

CoRR, 2024

RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold.

Amrith Setlur, Saurabh Garg, Xinyang Geng, Naman Garg, Virginia Smith, Aviral Kumar

CoRR, 2024

Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models.

Amrith Setlur, Saurabh Garg, Virginia Smith, Sergey Levine

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Deep Neural Networks Tend To Extrapolate Predictably.

Katie Kang, Amrith Setlur, Claire J. Tomlin, Sergey Levine

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features.

Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Leveraging Public Representations for Private Transfer Learning.

Pratiksha Thaker, Amrith Setlur, Zhiwei Steven Wu, Virginia Smith

CoRR, 2023

Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts.

Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

CoRR, 2023

Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.

Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn

CoRR, 2023

Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.

Saurabh Garg, Amrith Setlur, Zachary C. Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Contextual Reliability: When Different Features Matter in Different Contexts.

Gaurav Rohit Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan

Proceedings of the International Conference on Machine Learning, 2023

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Adversarial Unlearning: Reducing Confidence Along Adversarial Directions.

Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Lessons from Chasing Few-Shot Learning Benchmarks: Rethinking the Evaluation of Meta-Learning Methods.

Amrith Setlur, Oscar Li, Virginia Smith

CoRR, 2021

Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution.

Amrith Setlur, Oscar Li, Virginia Smith

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Explaining the Efficacy of Counterfactually Augmented Data.

Divyansh Kaushik, Amrith Setlur, Eduard H. Hovy, Zachary Chase Lipton

Proceedings of the 9th International Conference on Learning Representations, 2021

Towards Using Heterogeneous Relation Graphs for End-to-End TTS.

Amrith Setlur, Aman Madaan, Tanmay Parekh, Yiming Yang, Alan W. Black

Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021

2020

Is Support Set Diversity Necessary for Meta-Learning?

Amrith Setlur, Oscar Li, Virginia Smith

CoRR, 2020

Covariate Distribution Aware Meta-learning.

Amrith Setlur, Saket Dingliwal, Barnabás Póczos

CoRR, 2020

ReStGAN: A step towards visually guided shopper experience via text-to-image synthesis.

Shiv Surya, Amrith Setlur, Arijit Biswas, Sumit Negi

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Nonlinear ISA with Auxiliary Variables for Learning Speech Representations.

Amrith Setlur, Barnabás Póczos, Alan W. Black

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Robust Handwriting Recognition with Limited and Noisy Data.

Hai Pham, Amrith Setlur, Saket Dingliwal, Tzu-Hsiang Lin, Barnabás Póczos, Kang Huang, Zhuo Li, Jae Lim, Collin McCormack, Tam Vu

Proceedings of the 17th International Conference on Frontiers in Handwriting Recognition, 2020

Politeness Transfer: A Tag and Generate Approach.

Aman Madaan, Amrith Setlur, Tanmay Parekh, Barnabás Póczos, Graham Neubig, Yiming Yang, Ruslan Salakhutdinov, Alan W. Black, Shrimai Prabhumoye

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Better Approximate Inference for Partial Likelihood Models with a Latent Structure.

Amrith Setlur, Barnabás Póczos

CoRR, 2019