Publications

2025

Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning
A. Setlur, N. Rajaraman, S. Levine, A. Kumar
ICML 2025 (Spotlight), ICLR VerifAI (Oral)
[pdf]
Scaling Test-Time Compute Without Verification or RL is Suboptimal
Y. Qu^*, M. Yang^*, A. Setlur, L. Tunstall, E. Beeching, R. Salakhutdinov, A. Kumar
ICML (2025), FM‑Wild ICLR 2025 (Oral)
[pdf] [blog post]
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
A. Setlur^*, C. Nagpal^*, A. Fisch, X. Geng, J. Eisenstein, R. Agarwal, A. Agarwal, J. Berant, A. Kumar
ICLR (2025) (Spotlight)
[pdf]

RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
A. Setlur, S. Garg, X. Geng, N. Garg, V. Smith, A. Kumar
NeurIPS (2024)
[pdf]
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
P. Thaker, A. Setlur, Z.S. Wu, V. Smith
NeurIPS (2024)
[pdf]
Prompting for Robustness: Extracting Robust Classifiers from Foundation Models
A. Setlur^*, S Garg^*, V Smith, S Levine
ICML (2024)
[pdf]
Project with Source, Probe with Target: Extracting Useful Features for Adaptation to Distribution Shifts
A.S. Chen^*, Y. Lee^*, A. Setlur, S. Levine, C Finn
ICLR (2024) (Spotlight)
[pdf]
The Optimal Constant Solution: Predictable Extrapolation in Deep Neural Networks
K. Kang, A. Setlur, C. Tomlin, S. Levine
ICLR (2024)
[pdf]

Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
S. Garg^*, A. Setlur^*, Z. Lipton, S. Balakrishnan, V. Smith, A. Raghunathan
NeurIPS 2023
[pdf]
Private and Personalized Histogram Estimation in a Federated Setting
A. Setlur, V Feldman, K Talwar
NeurIPS 2023
[pdf]
Leveraging public representations for private transfer learning
P Thaker, A. Setlur, ZS Wu, V Smith
NeurIPS 2023
[pdf]
Multitask Learning Can Improve Worst-Group Outcomes
A. Kulkarni^*, L. Dery^*, A. Setlur, A. Raghunathan, A .Talwalkar, G. Neubig
TMLR 2023
[pdf]
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts
A Chen, Y Lee, A. Setlur, S Levine, C Finn
ArXiv Preprint
[pdf]
Contextual Reliability: When Different Features Matter in Different Contexts
G. Ghosal^*, A. Setlur^*, D. Brown, A. Dragan, A. Raghunathan
ICML 2023
[pdf]
Bitrate-constrained DRO: Beyond worst case robustness to unknown group shifts
A. Setlur, D. Dennis, B. Eysenbach, A. Raghunathan, C. Finn, V. Smith, S. Levine
ICLR 2023
[pdf]

Adversarial Unlearning: Reducing Confidence Along Adversarial Directions
A. Setlur, B. Eysenbach, V. Smith, S. Levine
NeurIPS 2022
[pdf]

Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
A. Setlur^*, O. Li^*, V. Smith
NeurIPS 2021
[NeurIPS]
Is support set diversity necessary for meta-learning?
A. Setlur^*, O. Li^*, V. Smith
ArXiv Preprint
[pdf]
Explaining the efficacy of counterfactually augmented data
D. Kaushik, A. Setlur, E. Hovy, ZC. Lipton
ICLR 2021
[pdf]
Nonlinear ISA with auxiliary variables for learning speech representations
A. Setlur, B. Póczos, AW. Black
InterSpeech 2021 (Best Paper Nomination)
[pdf]
Towards Using Heterogeneous Relation Graphs for End-to-End TTS
A. Setlur^*^, A Madaan^*^, T Parekh^*^, Y Yang, AW Black
ASRU 2021
[pdf]

Politeness transfer: A tag and generate approach
A. Madaan^*^, A. Setlur^*^, T. Parekh^*^, B. Poczos, G. Neubig, Y. Yang, R. Salakhutdinov, A. W Black, S. Prabhumoye
ACL 2020
[pdf]
Robust handwriting recognition with limited and noisy data
H. Pham, A. Setlur, S. Dingliwal, T. Lin, B. Poczos, K. Huang, Z. Li, J. Lim, C. McCormack, T. Vu
ICFHR 2020
[pdf]
An efficient fault tolerant workflow scheduling approach using replication heuristics and checkpointing in the cloud
A. Setlur, S. Nirmala, H. Singh, S. Khoriya
Journal of Parallel and Distributed Computing
[pdf]
ReStGAN: A step towards visually guided shopper experience via text-to-image synthesis
S Surya, A. Setlur, A Biswas, S Negi
WACV 2020
[pdf]
Better Approximate Inference for Partial Likelihood Models with a Latent Structure
A. Setlur, B. Póczós
TPP @ Neurips 2019 (Oral)
[pdf]