Adish Singla

Corruption Robust Offline Reinforcement Learning with Human Feedback AISTATS 2025 Policy Teaching via Data Poisoning in Learning from Human Preferences AISTATS 2025 Program Synthesis Benchmark for Visual Programming in XLogoOnline Environment ACL 2025 Text-Diffusion Red-Teaming of Large Language Models: Unveiling Harmful Behaviors with Proximity Constraints AAAI 2025 Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming NeurIPS 2024 Corruption-Robust Offline Two-Player Zero-Sum Markov Games AISTATS 2024 Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation NeurIPS 2024 Learning Embeddings for Sequential Tasks Using Population of Agents IJCAI 2024 On the Complexity of Teaching a Family of Linear Behavior Cloning Learners NeurIPS 2024 Proximal Curriculum with Task Correlations for Deep Reinforcement Learning IJCAI 2024 Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences ICML 2024 Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning AISTATS 2023 Online Reinforcement Learning with Uncertain Episode Lengths AAAI 2023 Specifying and Testing k-Safety Properties for Machine-Learning Models IJCAI 2023 Admissible Policy Teaching through Reward Design AAAI 2022 Bayesian Persuasion in Sequential Decision-Making AAAI 2022 Envy-free Policy Teaching to Multiple Agents NeurIPS 2022 Exploration-Guided Reward Shaping for Reinforcement Learning under Sparse Rewards NeurIPS 2022 On Batch Teaching with Sample Complexity Bounded by VCD NeurIPS 2022 Provable Defense against Backdoor Policies in Reinforcement Learning NeurIPS 2022 Curriculum Design for Teaching via Demonstrations: Theory and Applications NeurIPS 2021 Explicable Reward Design for Reinforcement Learning Agents NeurIPS 2021 On Blame Attribution for Accountable Multi-Agent Sequential Decision Making NeurIPS 2021 Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks JMLR 2021 Teaching an Active Learner with Contrastive Examples NeurIPS 2021 Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm NeurIPS 2021 The Sample Complexity of Teaching by Reinforcement on Q-Learning AAAI 2021 The Teaching Dimension of Kernel Perceptron AISTATS 2021 Adaptive Reward-Poisoning Attacks against Reinforcement Learning ICML 2020 Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning ICML 2020 Synthesizing Tasks for Block-based Programming NeurIPS 2020 Task-agnostic Exploration in Reinforcement Learning NeurIPS 2020 Understanding the Power and Limitations of Teaching with Imperfect Knowledge IJCAI 2020 Efficient learning of smooth probability functions from Bernoulli tests with guarantees ICML 2019 Interactive Teaching Algorithms for Inverse Reinforcement Learning IJCAI 2019 Iterative Classroom Teaching AAAI 2019 Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints NeurIPS 2019 Learning to Collaborate in Markov Decision Processes ICML 2019 Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models NeurIPS 2019 Teaching Multiple Concepts to a Forgetful Learner NeurIPS 2019 Enhancing the Accuracy and Fairness of Human Decision Making NeurIPS 2018 Teaching Inverse Reinforcement Learners via Features and Demonstrations NeurIPS 2018 Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners NeurIPS 2018 Actively Learning Hemimetrics with Applications to Eliciting User Preferences ICML 2016 Building Hierarchies of Concepts via Crowdsourcing IJCAI 2015 Information Gathering in Networks via Active Exploration IJCAI 2015 Near-Optimally Teaching the Crowd to Classify ICML 2014