Abhishek Gupta

AMPS: ASR with Multimodal Paraphrase Supervision NAACL 2025 ATK: Automatic Task-driven Keypoint Selection for Robust Policy Learning CoRL 2025 DRAWER: Digital Reconstruction and Articulation With Environment Realism CVPR 2025 Evolvable Conditional Diffusion IJCAI 2025 HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation ICLR 2025 Making VLMs More Robot-Friendly: Self-Critical Distillation of Low-Level Procedural Reasoning EMNLP 2025 Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning ICLR 2025 RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies CoRL 2025 Robot Learning with Super-Linear Scaling RSS 2025 SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks ICLR 2025 Steering Your Diffusion Policy with Latent Space Reinforcement Learning CoRL 2025 STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning ICLR 2025 Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets RSS 2025 ASID: Active Exploration for System Identification in Robotic Manipulation ICLR 2024 CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning ICLR 2024 Distributional Successor Features Enable Zero-Shot Policy Optimization NeurIPS 2024 DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset RSS 2024 Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning ICLR 2024 Improving Self-supervised Pre-training using Accent-Specific Codebooks Interspeech 2024 Learning to Cooperate with Humans using Generative Agents NeurIPS 2024 Modeling Boundedly Rational Agents with Latent Inference Budgets ICLR 2024 Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL NeurIPS 2024 Parameter-efficient Adaptation of Multilingual Multimodal Models for Low-resource ASR EMNLP 2024 Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning NeurIPS 2024 Reconciling Reality through Simulation: A Real-To-Sim-to-Real Approach for Robust Manipulation RSS 2024 Teaching Robots with Show and Tell: Using Foundation Models to Synthesize Robot Policies from Language and Visual Demonstration CoRL 2024 URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images RSS 2024 Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback CoRL 2023 Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets NeurIPS 2023 Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback NeurIPS 2023 Cherry-Picking with Reinforcement Learning RSS 2023 Fighting Uncertainty with Gradients: Offline Reinforcement Learning via Diffusion Score Matching CoRL 2023 GenAug: Retargeting behaviors to unseen situations via Generative Augmentation RSS 2023 Guiding Pretraining in Reinforcement Learning with Large Language Models ICML 2023 Learning to Extrapolate: A Transductive Approach ICLR 2023 REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation CoRL 2023 RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability NeurIPS 2023 RoboHive: A Unified Framework for Robot Learning NeurIPS 2023 Self-Supervised Reinforcement Learning that Transfers using Random Features NeurIPS 2023 Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective COLT 2023 Autonomous Reinforcement Learning: Formalism and Benchmarking ICLR 2022 CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANs UAI 2022 Distributionally Adaptive Meta Reinforcement Learning NeurIPS 2022 Graph Learning Assisted Multi-Objective Integer Programming NeurIPS 2022 Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation CoRL 2022 Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity NeurIPS 2022 Weighted Gaussian Process Bandits for Non-stationary Environments AISTATS 2022 Adaptive Risk Minimization: Learning to Adapt to Domain Shift NeurIPS 2021 Autonomous Reinforcement Learning via Subgoal Curricula NeurIPS 2021 Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation CoRL 2021 Learning to Reach Goals via Iterated Supervised Learning ICLR 2021 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning ICML 2021 Teachable Reinforcement Learning via Advice Distillation NeurIPS 2021 Which Mutual-Information Representation Learning Objectives are Sufficient for Control? NeurIPS 2021 DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction NeurIPS 2020 Gradient Surgery for Multi-Task Learning NeurIPS 2020 The Ingredients of Real World Robotic Reinforcement Learning ICLR 2020 Automatically Composing Representation Transformations as a Means for Generalization ICLR 2019 Diversity is All You Need: Learning Skills without a Reward Function ICLR 2019 Guided Meta-Policy Search NeurIPS 2019 Guiding Policies with Language via Meta-Learning ICLR 2019 Learning Actionable Representations with Goal Conditioned Policies ICLR 2019 Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning CoRL 2019 ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots CoRL 2019 Unsupervised Curricula for Visual Meta-Reinforcement Learning NeurIPS 2019 Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations RSS 2018 Meta-Reinforcement Learning of Structured Exploration Strategies NeurIPS 2018 Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings ICML 2018