Narang, Adhyyan

9 publications

ICLR 2025 On Targeted Manipulation and Deception When Optimizing LLMs for User Feedback Marcus Williams, Micah Carroll, Adhyyan Narang, Constantin Weisser, Brendan Murphy, Anca Dragan

UAI 2024 Efficient Interactive Maximization of BP and Weakly Submodular Objectives Adhyyan Narang, Omid Sadeghi, Lillian Ratliff, Maryam Fazel, Jeff Bilmes

NeurIPS 2024 Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson

NeurIPSW 2024 Targeted Manipulation and Deception Emerge in LLMs Trained on User* Feedback Marcus Williams, Micah Carroll, Constantin Weisser, Brendan Murphy, Adhyyan Narang, Anca Dragan

JMLR 2023 Multiplayer Performative Prediction: Learning in Decision-Dependent Games Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff

AISTATS 2022 Learning in Stochastic Monotone Games with Decision-Dependent Data Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian Ratliff

JMLR 2021 Classification vs Regression in Overparameterized Regimes: Does the Loss Function Matter? Vidya Muthukumar, Adhyyan Narang, Vignesh Subramanian, Mikhail Belkin, Daniel Hsu, Anant Sahai

NeurIPS 2021 Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games Tanner Fiez, Lillian Ratliff, Eric Mazumdar, Evan Faulkner, Adhyyan Narang

NeurIPS 2021 Towards Sample-Efficient Overparameterized Meta-Learning Yue Sun, Adhyyan Narang, Ibrahim Gulluk, Samet Oymak, Maryam Fazel