| 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 |
| 2024 | ICLR | Think before you speak: Training Language Models With Pause Tokens. | Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan |
| 2024 | ICLR | The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning. | Tian Jin, Nolan Clement, Xin Dong, Vaishnavh Nagarajan, Michael Carbin, Jonathan Ragan-Kelley, Gintare Karolina Dziugaite |
| 2024 | ICLR | Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning. | Jacob Mitchell Springer, Vaishnavh Nagarajan, Aditi Raghunathan |
| 2024 | ICML | The Pitfalls of Next-Token Prediction. | Gregor Bachmann, Vaishnavh Nagarajan |
| 2022 | ICLR | Assessing Generalization of SGD via Disagreement. | Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter |
| 2021 | AISTATS | Provably Safe PAC-MDP Exploration Using Analogies. | Melrose Roderick, Vaishnavh Nagarajan, J. Zico Kolter |
| 2021 | ICLR | A Learning Theoretic Perspective on Local Explainability. | Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar |
| 2021 | ICLR | Understanding the failure modes of out-of-distribution generalization. | Vaishnavh Nagarajan, Anders Andreassen, Behnam Neyshabur |
| 2019 | AISTATS | Revisiting Adversarial Risk. | Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan, Pradeep Ravikumar |
| 2019 | ICLR | Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience. | Vaishnavh Nagarajan, J. Zico Kolter |
| 2018 | USENIX | Geriatrix: Aging what you see and what you don't see. A file system aging approach for modern storage systems. | Saurabh Kadekodi, Vaishnavh Nagarajan, Gregory R. Ganger |
| 2017 | ALT | Lifelong Learning in Costly Feature Spaces. | Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan |
| 2017 | COLT | Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems. | Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White |
| 2016 | WWW | Incorporating Side Information in Tensor Completion. | Hemank Lamba, Vaishnavh Nagarajan, Kijung Shin, Naji Shajarisales |
| 2015 | AAAI | Every Team Deserves a Second Chance: Identifying When Things Go Wrong (Student Abstract Version). | Vaishnavh Nagarajan, Leandro Soriano Marcolino, Milind Tambe |
| 2015 | AAAI | Every Team Makes Mistakes: An Initial Report on Predicting Failure in Teamwork. | Vaishnavh Nagarajan, Leandro Soriano Marcolino, Milind Tambe |