Adith Swaminathan

63 papers A* 15A 7C 1Misc 1Journal 32Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs. AAAI Trenton Chang, Tobias Schnabel, Adith Swaminathan, Jenna Wiens
2026	J	`jnl`	Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs. CoRR Kiran Tomlinson, Tobias Schnabel, Adith Swaminathan, Jennifer Neville
2026	J	`jnl`	Understanding the Challenges in Iterative Generative Optimization with LLMs. CoRR Allen Nie, Xavier Daull, Zhiyi Kuang, Abhinav Akkiraju, Anish Chaudhuri, Max Piasevoli, Ryan Rong, Yucheng Yuan, Prerit Choudhary, Shannon Xiao, Rasool Fakoor, Adith Swaminathan, Ching-An Cheng
2025	J	`jnl`	A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs. CoRR Trenton Chang, Tobias Schnabel, Adith Swaminathan, Jenna Wiens
2025	J	`jnl`	Lost in Transmission: When and Why LLMs Fail to Reason Globally. CoRR Tobias Schnabel, Kiran Tomlinson, Adith Swaminathan, Jennifer Neville
2025	J	`jnl`	Provably Learning from Language Feedback. CoRR Wanqiao Xu, Allen Nie, Ruijie Zheng, Aditya Modi, Adith Swaminathan, Ching-An Cheng
2024	J	`jnl`	AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks. CoRR Jiacen Xu, Jack W. Stokes, Geoff McDonald, Xuesong Bai, David Marshall, Siyue Wang, Adith Swaminathan, Zhou Li
2024	J	`jnl`	Combining Open-box Simulation and Importance Sampling for Tuning Large-Scale Recommenders. CoRR Kaushal Paneri, Michael Munje, Kailash Singh Maurya, Adith Swaminathan, Yifan Shi
2024	A*	`conf`	How to Solve Contextual Goal-Oriented Problems with Offline Datasets? NeurIPS Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng
2024	J	`jnl`	How to Solve Contextual Goal-Oriented Problems with Offline Datasets? CoRR Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng
2024	A	`conf`	On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots. UAI Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
2024	J	`jnl`	On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots. CoRR Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
2024	J	`jnl`	The Importance of Directional Feedback for LLM-based Optimizers. CoRR Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2024	J	`jnl`	Trace is the New AutoDiff - Unlocking Efficient Optimization of Computational Workflows. CoRR Ching-An Cheng, Allen Nie, Adith Swaminathan
2024	A*	`conf`	Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs. NeurIPS Ching-An Cheng, Allen Nie, Adith Swaminathan
2023	A*	`conf`	Hindsight Learning for MDPs with Exogenous Inputs. ICML Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo de Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
2023	J	`jnl`	Interactive Robot Learning from Verbal Correction. CoRR Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
2023	J	`jnl`	LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
2022	J	`jnl`	Hindsight Learning for MDPs with Exogenous Inputs. CoRR Sean R. Sinclair, Felipe Frujeri, Ching-An Cheng, Adith Swaminathan
2021	A*	`conf`	Heuristic-Guided Reinforcement Learning. NeurIPS Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2021	J	`jnl`	Heuristic-Guided Reinforcement Learning. CoRR Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2021	J	`jnl`	Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL. CoRR Bogdan Mazoure, Paul Mineiro, Pavithra Srinath, Reza Sharifi Sedeh, Doina Precup, Adith Swaminathan
2021	J	`jnl`	Recommendations as Treatments. AI Mag. Thorsten Joachims, Ben London, Yi Su, Adith Swaminathan, Lequn Wang
2020	—	`conf`	Active Learning for ML Enhanced Database Systems. SIGMOD Conference Lin Ma, Bailu Ding, Sudipto Das, Adith Swaminathan
2020	J	`jnl`	Improved Image Wasserstein Attacks and Defenses. CoRR J. Edward Hu, Adith Swaminathan, Hadi Salman, Greg Yang
2020	A*	`conf`	Learning Calibratable Policies using Programmatic Style-Consistency. ICML Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
2020	A*	`conf`	Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations. AAAI Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz
2020	A*	`conf`	Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration. NeurIPS Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2020	J	`jnl`	Provably Good Batch Reinforcement Learning Without Great Exploration. CoRR Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2020	A	`conf`	REVEAL 2020: Bandit and Reinforcement Learning from User Interactions. RecSys Thorsten Joachims, Yves Raimond, Olivier Koch, Maria Dimakopoulou, Flavian Vasile, Adith Swaminathan
2020	A*	`conf`	Working Memory Graphs. ICML Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
2019	A*	`conf`	A Distillation Approach to Data Efficient Individual Treatment Effect Estimation. AAAI Maggie Makar, Adith Swaminathan, Emre Kiciman
2019	J	`jnl`	Learning Calibratable Policies using Programmatic Style-Consistency. CoRR Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
2019	J	`jnl`	Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations. CoRR Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz
2019	J	`jnl`	Multi-Preference Actor Critic. CoRR Ishan Durugkar, Matthew J. Hausknecht, Adith Swaminathan, Patrick MacAlpine
2019	J	`jnl`	NAIL: A General Interactive Fiction Agent. CoRR Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams
2019	J	`jnl`	Off-Policy Policy Gradient with State Distribution Correction. CoRR Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2019	A	`conf`	Off-Policy Policy Gradient with Stationary Distribution Correction. UAI Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2019	A	`conf`	REVEAL 2019: closing the loop with the real world: reinforcement and robust estimators for recommendation. RecSys Thorsten Joachims, Maria Dimakopoulou, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile
2019	J	`jnl`	Working Memory Graphs. CoRR Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
2018	—	`conf`	Deep Learning with Logged Bandit Feedback. ICLR (Poster) Thorsten Joachims, Adith Swaminathan, Maarten de Rijke
2018	A	`conf`	REVEAL 2018: offline evaluation for recommender systems. RecSys Thorsten Joachims, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile
2018	A*	`conf`	Unbiased Learning-to-Rank with Biased Feedback. IJCAI Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
2017	—	`—`	Counterfactual evaluation and learning from logged user feedback. Adith Swaminathan
2017	—	`conf`	Off-policy evaluation for slate recommendation. NIPS Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
2017	A	`conf`	Unbiased Learning-to-Rank with Biased Feedback. WSDM Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
2016	A*	`conf`	Counterfactual Evaluation and Learning for Search, Recommendation and Ad Placement. SIGIR Thorsten Joachims, Adith Swaminathan
2016	J	`jnl`	Large-scale Validation of Counterfactual Learning Methods: A Test-Bed. CoRR Damien Lefortier, Adith Swaminathan, Xiaotao Gu, Thorsten Joachims, Maarten de Rijke
2016	J	`jnl`	Off-policy evaluation for slate recommendation. CoRR Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni
2016	A*	`conf`	Recommendations as Treatments: Debiasing Learning and Evaluation. ICML Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
2016	J	`jnl`	Recommendations as Treatments: Debiasing Learning and Evaluation. CoRR Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims
2016	Misc	`conf`	Unbiased Comparative Evaluation of Ranking Functions. ICTIR Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
2016	J	`jnl`	Unbiased Comparative Evaluation of Ranking Functions. CoRR Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims
2016	J	`jnl`	Unbiased Learning-to-Rank with Biased Feedback. CoRR Thorsten Joachims, Adith Swaminathan, Tobias Schnabel
2015	J	`jnl`	Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. Adith Swaminathan, Thorsten Joachims
2015	—	`conf`	Counterfactual Risk Minimization. WWW (Companion Volume) Adith Swaminathan, Thorsten Joachims
2015	A*	`conf`	Counterfactual Risk Minimization: Learning from Logged Bandit Feedback. ICML Adith Swaminathan, Thorsten Joachims
2015	J	`jnl`	Counterfactual Risk Minimization: Learning from Logged Bandit Feedback. CoRR Adith Swaminathan, Thorsten Joachims
2015	—	`conf`	The Self-Normalized Estimator for Counterfactual Learning. NIPS Adith Swaminathan, Thorsten Joachims
2015	—	`conf`	Unbiased Ranking Evaluation on a Budget. WWW (Companion Volume) Tobias Schnabel, Adith Swaminathan, Thorsten Joachims
2014	C	`conf`	Mining Videos from the Web for Electronic Textbooks. ICFCA Rakesh Agrawal, Maria Christoforaki, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi, Adith Swaminathan
2013	A*	`conf`	Beyond myopic inference in big data pipelines. KDD Karthik Raman, Adith Swaminathan, Johannes Gehrke, Thorsten Joachims
2012	A	`conf`	Temporal corpus summarization using submodular word coverage. CIKM Ruben Sipos, Adith Swaminathan, Pannaga Shivaswamy, Thorsten Joachims