Adith Swaminathan
19 papers · 2015–2026 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (45) π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Grand Slam
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Keyword Champion
(2)
π§
Keyword Pioneer
π
Renaissance Researcher
(7)
π₯
Unstoppable Β· Bronze
β
The Questioner
π
Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
ποΈ
Keyword Collector
(101)
Top co-authors
Research topics
Machine Learning
(15)
Learning Types
(11)
Artificial Intelligence
(10)
Reinforcement Learning
(9)
Core AI
(9)
Methods
(8)
Optimization & Theory
(8)
Deep Learning
(3)
Application Areas
(3)
Applications Β· Reinforcement Learning
(3)
Core Methods
(3)
Computer Science
(2)
Data Science & Analytics
(2)
Applications Β· Data Science & Analytics
(2)
Applications Β· Computer Science
(2)
Keywords
reinforcement learning
(5)
policy learning
(4)
counterfactual risk minimization
(4)
large language model
(3)
importance sampling
(3)
markov decision process
(2)
policy gradient
(2)
logged bandit feedback
(2)
causal inference
(2)
policy optimization
(2)
propensity scoring
(2)
bandit feedback
(2)
offline reinforcement learning
(2)
multi-label classification
(2)
counterfactual learning
(2)
prompt engineering
(1)
sequential decision making
(1)
object recognition
(1)
off-policy evaluation
(1)
transformer architecture
(1)
Papers
A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs
AAAI 2026
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
NeurIPS 2024
On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots
UAI 2024
Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs
NeurIPS 2024
Hindsight Learning for MDPs with Exogenous Inputs
ICML 2023
Heuristic-Guided Reinforcement Learning
NeurIPS 2021
Learning Calibratable Policies using Programmatic Style-Consistency
ICML 2020
Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations
AAAI 2020
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration
NeurIPS 2020
Working Memory Graphs
ICML 2020
A Distillation Approach to Data Efficient Individual Treatment Effect Estimation
AAAI 2019
Off-Policy Policy Gradient with Stationary Distribution Correction
UAI 2019
Deep Learning with Logged Bandit Feedback
ICLR 2018
Unbiased Learning-to-Rank with Biased Feedback
IJCAI 2018
Off-policy evaluation for slate recommendation
NeurIPS 2017
Recommendations as Treatments: Debiasing Learning and Evaluation
ICML 2016
Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization
JMLR 2015
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback
ICML 2015
The Self-Normalized Estimator for Counterfactual Learning
NeurIPS 2015