Imitation Learning

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Imitation Learning

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Imitation

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Motion Imitation

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Teacher-Student Representational Alignment for Reinforcement Learning-Driven Imitation Learning
May 27, 2026Meraj Mammadov, Pedro Zuidberg Dos Martires, Johannes Andreas StorkImitation Learning Imitation
ROSD: Reflective On-Policy Self-Distillation for Language Model Reasoning across Domains
May 27, 2026Ziqi Zhao, Xinyu Ma, Liu Yang +6Unsupervised On-Policy Self-Distillation Large Language Model Reasoning
SPAR: Support-Preserving Action Rectification
May 27, 2026Jiaxin Zhao, Weihang Pan, Xun Liang +1Imitation Learning Rectification
HumanoidMimicGen: Data Generation for Loco-Manipulation via Whole-Body Planning
May 26, 2026Kevin Lin, Ajay Mandlekar, Caelan Reed Garrett +7Humanoid Loco-Manipulation Motion Imitation
TPS-Drive: Task-Guided Representation Purification for VLM-based Autonomous Driving
May 26, 2026Jiaxiang Li, Yumao Liu, Ke MaAutonomous Driving Trajectory Prediction
Less is More: Early Stopping Rollout for On-Policy Distillation
May 26, 2026Zhou Ziheng, Jiaqi Li, Huacong Tang +2On-Policy Distillation Off-Policy Evaluation
On the Generalization Capabilities, Design Choices and Limitations of Keypoint Imitation Learning
May 26, 2026Thomas Lips, Marco Moletta, Michael C. Welle +2Imitation Learning Keypoint Detection
MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control
May 25, 2026Bin Li, Ruichi Zhang, Han Liang +4Long-Tail Humanoid Whole-Body Control Imitation Learning
How to Mitigate the Distribution Shift Problem in Robotics Control: A Robust and Adaptive Approach Based on Offline to Online Imitation Learning
May 25, 2026Hyung-Suk Yoon, Seung-Woo SeoImitation Learning Distribution Shifts
InvariantCloud: A Globally Invariant, Uniquely Indexed Point Cloud Framework for Robust 6-DoF Tactile Pose Tracking
May 24, 2026Pengfei Ye, Yuxiang Ma, Yi Zhou +3Category-Level Object Pose Estimation 6-Dof
Beyond the Target: From Imitation to Collaboration in Speculative Decoding
May 24, 2026Jinze Li, Yixing Xu, Guanchen Li +7Speculative Decoding LLM Inference Efficiency
Neuro-Inspired Inverse Learning for Planning and Control
May 22, 2026Maryna Kapitonova, Tonio BallInverse Dynamics Inference-Time Control
Instrumentation for Imitation Learning: Enhancing Training Datasets for Clothes Hanger Insertion
May 22, 2026Remko Proesmans, Thomas Lips, Francis wyffelsImitation Learning Teleoperation
Direct Dynamic Retargeting for Humanoid Imitation Learning from Videos
May 22, 2026Constant Roux, Ludovic De Matteïs, Armand Jordana +4Motion Retargeting Motion Imitation
SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-based Humanoid Control
May 21, 2026Jingyan Zhang, Han Liang, Ruichi Zhang +6Long-Tail Humanoid Whole-Body Control Diffusion Policies
From Patches to Trajectories: Privileged Process Supervision for Software-Engineering Agents
May 21, 2026Murong Ma, Tianyu Chen, Yun Lin +7Swe-Bench Verified Supervised Fine-Tuning
Mobile UMI: Cross-View Diffusion Policy with Decoupled Kinematics for Mobile Manipulation
May 20, 2026Haoran Huang, Haonan Dong, Huixu DongMotion Imitation Imitation Learning
VLA-REPLICA: A Low-Cost, Reproducible Benchmark for Real-World Evaluation of Vision-Language-Action Models
May 20, 2026Alex S. Huang, Jiahui Zhang, Shiqing Tang +1Robotic Datasets Generalizable Robotic Manipulations
GaussianDream: A Feed-Forward 3D Gaussian World Model for Robotic Manipulation
May 20, 2026Zijian Zhang, Yuqing Jiang, Qian Cheng +6Feed-Forward 3D Gaussian Reconstruction Imitation Learning
Spacetime Optimal-Transport Attention for Visuo-Haptic Imitation Learning of Contact-Rich Manipulation
May 19, 2026Yue Feng, Weicheng Huang, I-Ming ChenMotion Imitation Actuator
Beyond Action Residuals: Real-World Robot Policy Steering via Bottleneck Latent Reinforcement Learning
May 19, 2026Dongjie Yu, Kun Lei, Zhennan Jiang +2Robot Policies Imitation Learning
Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark
May 19, 2026Yang Fu, Haomin Bao, Rohit Sonker +4Plasma Shape Control Joint Reinforcement Learning
Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
May 19, 2026Junli Wang, Zhihua Hua, Xueyi Liu +7Autonomous Driving Imitation Learning
COBALT: Crowdsourcing Robot Learning via Cloud-Based Teleoperation with Smartphones
May 18, 2026Ayush Agarwal, Ansh Gandhi, Jeremy A. Collins +6Teleoperation Scalable Robot Learning
From Imitation to Interaction: Mastering Game of Schnapsen with Shallow Reinforcement Learning
May 16, 2026Ján Klačan, Sizhong ZhangDeep Reinforcement Learning Imitation
When Dynamics Shift, Robust Task Inference Wins: Offline Imitation Learning with Behavior Foundation Models Revisited
May 16, 2026Rishabh Agrawal, Rahul Jain, Ashutosh NayyarImitation Learning Worst-Case
Offline Semantic Guidance for Efficient Vision-Language-Action Policy Distillation
May 15, 2026Jin Shi, Brady Zhang, Yishun LuVision-Language-Action Models Action Space
Imitation learning for clinical decision support in pediatric ECMO
May 15, 2026Fateme Golivand, Michael Skinner, Saurabh Mathur +5Intensive Care Unit Clinical Decision Support
Learning Sim-Grounded Policies for Bimanual Rope Manipulation from Human Teleoperation Data
May 15, 2026Gina Wigginghaus, Tim Missal, Berk Guler +2Robotic Manipulation Policies Bimanual Manipulation
Learning Bilevel Policies over Symbolic World Models for Long-Horizon Planning
May 15, 2026Dillon Z. Chen, Till Hofmann, Toryn Q. Klassen +1Long-Horizon Planning Imitation Learning
GAP: Geometric Anchor Pre-training for Data-Efficient Visuomotor Learning of Manipulation Tasks
May 15, 2026Davide Buoso, Andrea Protopapa, Stefano Di Carlo +2Visuomotor Policy Imitation Learning
SkiP: When to Skip and When to Refine for Efficient Robot Manipulation
May 15, 2026Mingtong Dai, Guanqi Peng, Yongjie Bai +5Generalizable Robotic Manipulations Imitation
Video Models Can Reason with Verifiable Rewards
May 14, 2026Tinghui Zhu, Sheng Zhang, James Y. Huang +5Video-Language Models Reinforcement Learning With Verifiable Reward
Diffusion Policy for Coordinated Control of a Nonholonomic Mobile Base and Dual Arms in Door Opening and Passing
May 14, 2026Shangqun Yu, Matthew En, Daniel Wu +4Visuomotor Policy Diffusion Policies
DSSP: Diffusion State Space Policy with Full-History Encoding
May 14, 2026Zhiyuan Guan, Jianshu Hu, Han Fang +5Diffusion Policies Imitation Learning
Ergodic Imitation for Adaptive Exploration around Demonstrations
May 13, 2026Ziyi Xu, Cem Bilaloglu, Yiming Li +1Imitation Learning Robot Trajectories
RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation
May 13, 2026Chengzhi Shen, Weixiang Shen, Tobias Susetzky +8Intensive Care Unit Patient Trajectories
Real-Time Whole-Body Teleoperation of a Humanoid Robot Using IMU-Based Motion Capture with Sim2Sim and Sim2Real Validation
May 12, 2026Hamza Ahmed Durrani, Suleman KhanTeleoperation Sim-To-Real Gap
Morphologically Equivariant Flow Matching for Bimanual Mobile Manipulation
May 12, 2026Max Siebenborn, Daniel Ordoñez Apraez, Sophie Lueth +4Bimanual Manipulation Robotic Manipulation Policies
Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation
May 12, 2026Ziyad Sheebaelhamd, Luca Viano, Volkan Cevher +1Imitation Learning Behavior Cloning
NavOL: Navigation Policy with Online Imitation Learning
May 12, 2026Xiaofei Wei, Chun Gu, Li ZhangEmbodied Navigation Imitation Learning
Coordinated Diffusion: Generating Multi-Agent Behavior Without Multi-Agent Demonstrations
May 12, 2026Lasse Peters, Laura Ferranti, Andrea Bajcsy +1Diffusion Policies Imitation Learning
Dynamic Full-body Motion Agent with Object Interaction via Blending Pre-trained Modular Controllers
May 12, 2026Sanghyeok Nam, Byoungjun Kim, Daehyung Park +1Articulated Objects Human Motion Generation
gym-invmgmt: An Open Benchmarking Framework for Inventory Management Methods
May 12, 2026Reza Barati, Qinmin Vivian HuMonotonic Inventory Estimation Reinforcement-Learning Policies
SEVO: Semantic-Enhanced Virtual Observation for Robust VLA Manipulation via Active Illumination and Data-Centric Collection
May 11, 2026Tianchonghui Fang, Yuan Zhuang, Fei MiaoVision-Language-Action Models Imitation Learning
Data-Asymmetric Latent Imagination and Reranking for 3D Robotic Imitation Learning
May 11, 2026Lianghao Luo, Xizhou Bu, Ruyan Liu +5Motion Imitation Imagination
Adaptive Action Chunking via Multi-Chunk Q Value Estimation
May 11, 2026Yongjae Shin, Jongseong Chae, Seongmin Kim +2Offline Reinforcement Learning Action Chunks
Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
May 10, 2026Anish Diwan, Davide Tateo, Christopher E. Mower +3Entropy Regularized Reinforcement Learning Imitation Learning
Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift
May 9, 2026Surbhi Goel, Jonathan Pei, James WangImitation Learning Behavior Cloning
Constraint-Aware Diffusion Priors for High-Fidelity and Versatile Quadruped Locomotion
May 9, 2026Jianhui Chen, Ruixin Zhan, Liu Liu +2Adversarial Motion Priors Diffusion Policies
A Visuo-Tactile Data Collection System with Haptic Feedback for Coarse-to-Fine Imitation Learning
May 9, 2026Yeseung Kim, Nayoung Oh, Jun Park +2Haptic Feedback Imitation Learning
Zero-shot Imitation Learning by Latent Topology Mapping
May 8, 2026Maxwell J. Jacobson, Yexiang XueImitation Learning Imitation
On Distinguishing Capability Elicitation from Capability Creation in Post-Training: A Free-Energy Perspective
May 8, 2026Yuhao Li, Shengchao LiuLLM Post-Training Methods Elicitation
TAVIS: A Benchmark for Egocentric Active Vision and Anticipatory Gaze in Imitation Learning
May 8, 2026Giacomo SpiglerImitation Learning Viewpoint-Dependent Active Perception
Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding
May 8, 2026Valeriy Vyaltsev, Alsu Sagirova, Anton Andreychuk +5Multi-Agent Path Finding Multi-Robot Motion Planning
How to Utilize Failure Demo Data?: Effective Data Selection for Imitation Learning Using Distribution Differences in Attention Mechanism
May 8, 2026Kana Miyamoto, Kanata Suzuki, Tetsuya OgataImitation Learning Scalable Robot Data Synthesis
Neurosymbolic Imitation Learning with Human Guidance: A Privileged Information Approach
May 8, 2026Nikhilesh Prabhakar, Varun Balaji, Athresh Karanam +2Imitation Learning Neuro-Symbolic Framework
Causal-Aware Foundation-Model for Bilevel Optimization in Discrete Choice Settings
May 7, 2026Shivaram Subramanian, Zhengliang Xue, Markus Ettl +2Discrete Choice Models Prices
ReActor: Reinforcement Learning for Physics-Aware Motion Retargeting
May 7, 2026David Müller, Agon Serifi, Sammy Christen +3Motion Retargeting Motion Imitation
Asymmetric On-Policy Distillation: Bridging Exploitation and Imitation at the Token Level
May 7, 2026Nan Jia, Haojin Yang, Xing Ma +6On-Policy Distillation Policy Gradient

May 27, 2026 · cs.LGJ/K move · Enter open · S save

Teacher-Student Representational Alignment for Reinforcement Learning-Driven Imitation Learning

Meraj Mammadov, Pedro Zuidberg Dos Martires, Johannes Andreas Stork

Department of Computer Science Örebro University

Imitation learning (IL) from a state-based reinforcement learning (RL) policy is a common approach to overcome the curse of dimensionality in complex and high-dimensional observation spaces prevalent in robotics. This paper addresses the irreducible imitation gap that emerges when teacher and student are learned in isolation, and the teacher policy has the liberty to rely on privileged state information that the student cannot infer from its observations. Instead of improving poor student performance with RL finetuning after IL, which often requires a whole new training setup, we propose a novel algorithm which learns a shared embedding space that hides agent-specific observations and thus trains imitable teacher policies by construction. We train the shared embedding space with self-supervised contrastive learning in parallel to the teacher policy and prevent it from extracting private information by limiting its gradients from updating the encoder networks. We perform evaluations on several example domains and compare to state-of-the-art baselines showing that our algorithm enables higher student performance with substantially reduced imitation gap.

Imitation Learning Imitation Teacher-Student Log-Probability Gap Contrastive Learning

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