← Authors

Adish Singla

47 papers · 2014–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (11) 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (14) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (9) πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏠 Conference Loyalist (20) 🀝 Dynamic Duo (16) 🧬 Topic Evolution πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (3) πŸš€ Conference Pioneer ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (189) πŸ“ˆ Trend Setter πŸ’Ž Century Club (47) πŸ”₯ Unstoppable (8)

Conferences

NIPS (20) ICML (7) IJCAI (7) AAAI (6) AISTATS (5) ACL (1) JMLR (1)

Top co-authors

Goran Radanovic (16) Rati Devidze (9) Parameswaran Kamalaruban (9) Yuxin Chen (7) Xiaojin Zhu (7) Andreas Krause (5) Debmalya Mandal (5) Andi Nika (5) Jiarui Gan (4) Xuezhou Zhang (4)

Research topics

Applications (2) Privacy (2) Education (2)

Keywords

reinforcement learning (10) sample complexity (7) machine teaching (6) active learning (6) inverse reinforcement learning (5) teaching algorithm (5) teaching dimension (4) policy teaching (3) concept learning (3) large language model (3) visual programming (3) reward function (3) regret bound (3) online learning (3) optimal policy (3) policy learning (3) markov decision process (3) adversarial attack (3) teaching complexity (3) multi-agent system (3)

Papers

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