Swaminathan, Adith

27 publications

NeurIPS 2025 Lost in Transmission: When and Why LLMs Fail to Reason Globally Tobias Schnabel, Kiran Tomlinson, Adith Swaminathan, Jennifer Neville

NeurIPS 2024 How to Solve Contextual Goal-Oriented Problems with Offline Datasets? Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng

ICLRW 2024 LLF-Bench: Benchmark for Interactive Learning from Language Feedback Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan

NeurIPSW 2024 Measuring Steerability in Large Language Models Trenton Chang, Jenna Wiens, Tobias Schnabel, Adith Swaminathan

UAI 2024 On Overcoming Miscalibrated Conversational Priors in LLM-Based ChatBots Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan

ICMLW 2024 Trace Is the New AutoDiff — Unlocking Efficient Optimization of Computational Workflows Ching-An Cheng, Allen Nie, Adith Swaminathan

NeurIPS 2024 Trace Is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs Ching-An Cheng, Allen Nie, Adith Swaminathan

ICML 2023 Hindsight Learning for MDPs with Exogenous Inputs Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo De Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan

NeurIPSW 2023 Importance of Directional Feedback for LLM-Based Optimizers Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan

NeurIPSW 2023 Simple Data Sharing for Multi-Tasked Goal-Oriented Problems Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng

NeurIPSW 2023 Simple Data Sharing for Multi-Tasked Goal-Oriented Problems Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng

ICMLW 2023 Towards Modular Machine Learning Pipelines Aditya Modi, Jivat Neet Kaur, Maggie Makar, Pavan Mallapragada, Amit Sharma, Emre Kiciman, Adith Swaminathan

NeurIPS 2021 Heuristic-Guided Reinforcement Learning Ching-An Cheng, Andrey Kolobov, Adith Swaminathan

ICML 2020 Learning Calibratable Policies Using Programmatic Style-Consistency Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht

AAAI 2020 Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz

NeurIPS 2020 Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

ICML 2020 Working Memory Graphs Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht

AAAI 2019 A Distillation Approach to Data Efficient Individual Treatment Effect Estimation Maggie Makar, Adith Swaminathan, Emre Kiciman

ICMLW 2019 Off-Policy Policy Gradient with State Distribution Correction Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

UAI 2019 Off-Policy Policy Gradient with Stationary Distribution Correction Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

ICLR 2018 Deep Learning with Logged Bandit Feedback Thorsten Joachims, Adith Swaminathan, Maarten de Rijke

IJCAI 2018 Unbiased Learning-to-Rank with Biased Feedback Thorsten Joachims, Adith Swaminathan, Tobias Schnabel

NeurIPS 2017 Off-Policy Evaluation for Slate Recommendation Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miro Dudik, John Langford, Damien Jose, Imed Zitouni

ICML 2016 Recommendations as Treatments: Debiasing Learning and Evaluation Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims

JMLR 2015 Batch Learning from Logged Bandit Feedback Through Counterfactual Risk Minimization Adith Swaminathan, Thorsten Joachims

ICML 2015 Counterfactual Risk Minimization: Learning from Logged Bandit Feedback Adith Swaminathan, Thorsten Joachims

NeurIPS 2015 The Self-Normalized Estimator for Counterfactual Learning Adith Swaminathan, Thorsten Joachims