Cross-Embodiment Robot Learning

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52 papers in the last four weeks, up 550% on the four weeks before. 0.5% of all new papers.

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SeeTraceAct: Visibility-Aware Latent Planning from Cross-Embodiment Demonstration Videos
Jun 1, 2026Jaehyeon Son, Junhyun Kim, Kyle Kam +7Robot Skill Learning Generalization in Robotic Manipulation
Georgia Institute of Technology · Allen Institute for AI · Johns Hopkins University +1
Dexterity-BEV: Aligning 3D World and Actions for Generalizable Robot Policies Learning
Jun 1, 2026Huayi Zhou, Wei Gao, Dekun Lu +12Generalization in Robotic Manipulation Cross-Embodiment Robot Learning
1DexForce Technology · 2The Chinese University of Hong Kong, Shenzhen
Co-training with Ego-centric Video and Demonstration for Robot Navigation Task
Jun 1, 2026Shoya Kuno, Yumo Ouchi, Kanata SuzukiMobile Robotics Robot Navigation
Spatial Robotics Research Center, Fujitsu Limited., Kanagawa 211-8588, Japan.
PHASOR: Phase-Anchored Universal Action Representations for Humanoid Embodiments
Jun 1, 2026Kihyun Kim, Chaeyun Kim, Jongho Shin +4Latent Action Learning Representation Learning
AIM Intelligence · Seoul National University · LG Electronics +2
GraspGen-X: Cross-Embodiment 6-DOF Diffusion-based Grasping
May 31, 2026Beining Han, Yu-Wei Chao, Erwin Coumans +5Robotic Grasping Generalization in Robotic Manipulation
1NVIDIA · 2Princeton University
Shape Your Body: Value Gradients for Multi-Embodiment Robot Design
May 30, 2026Nico Bohlinger, Jan PetersCross-Embodiment Robot Learning Robotic RL
Technical University of Darmstadt, Germany · Robotics Institute Germany (RIG); German Research Center for AI (DFKI); hessian.AI
HARP-VLA: Human-Robot Aligned Representation Learning for Vision-Language-Action Model
May 29, 2026Xiang Zhu, Puzhen Yuan, Yichen Liu +1Cross-Embodiment Robot Learning Robotic Manipulation
Institute for Interdisciplinary Information Sciences, Tsinghua University, China · Shanghai Qi Zhi Institute, China
Wall-OSS-0.5 Technical Report
May 29, 2026Ryan Yu, Pushi Zhang, Starrick Liu +24Zero-Shot Robotic Manipulation Cross-Embodiment Robot Learning
X Square Robot Team
Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments
May 28, 2026Qiuyue Wang, Mingsheng Li, Jian Guan +37Language-Conditioned Robot Manipulation Robot Foundation Models
Qwen Team
MonoDuo: Using One Robot Arm to Learn Bimanual Policies
May 28, 2026Sandeep Bajamahal, Lawrence Yunliang Chen, Toru Lin +3Bimanual Robotic Manipulation Cross-Embodiment Robot Learning
University of California, Berkeley
Turning Video Models into Generalist Robot Policies
May 27, 2026Sizhe Lester Li, Evan Kim, Xingjian Bai +4Robot Policy Learning Cross-Embodiment Robot Learning
1MIT · 2Independent Researcher · 3CMU +1
X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models
May 24, 2026Boyu Li, Chaoyi Xu, Haoqi Yuan +5Cross-Embodiment Robot Learning Diffusion Policy
1SKL-MAIS, Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · 3Beijing Academy of Artificial Intelligence +2
HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos
May 24, 2026Zhi Wang, Botao He, Kelin Yu +4Zero-Shot Learning Zero-Shot Robotic Manipulation
University of Maryland
ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots
May 22, 2026Yibin Wang, Muhan Li, Zihan Guo +1Robot Morphology-Control Co-Design Mixture of Experts
Northwestern University, Evanston, IL, USA.
Any2Any: Efficient Cross-Embodiment Transfer for Humanoid Whole-Body Tracking
May 22, 2026Ming Yang, Tao Yu, Feng Li +1Humanoid Robot Control Cross-Embodiment Robot Learning
LimX Dynamics
Demo-JEPA: Joint-Embedding Predictive Architecture for One-shot Cross-Embodiment Imitation
May 20, 2026Jingyang He, Guangrun Li, Jieyu Zhang +3Robot Skill Learning World Models for Robotics
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University · Beijing Innovation Center of Humanoid Robotics · University of Washington
Beyond Waypoints: Dual-Heatmap Grounding for Cross-Embodiment Semantic Navigation
May 19, 2026Kaijie Yun, Yue ChenCross-Embodiment Robot Learning Vision-Language Navigation
Harbin Institute of Technology · JD AI Research
From Human Videos to Robot Manipulation: A Survey on Scalable Vision-Language-Action Learning with Human-Centric Data
May 18, 2026Zhiyuan Feng, Qixiu Li, Huizhi Liang +12Language-Conditioned Robot Manipulation Cross-Embodiment Robot Learning
1Tsinghua University · 5Microsoft Research Asia · 2HKUST +4
LACE: Latent Visual Representation for Cross-Embodiment Learning
May 16, 2026Yoo Sung Jang, Kanchana Ranasinghe, Cristina Mata +3Cross-Embodiment Robot Learning Robot Imitation Learning
Stony Brook University · Salesforce AI Research
RIO: Flexible Real-Time Robot I/O for Cross-Embodiment Robot Learning
May 12, 2026Pablo Ortega-Kral, Eliot Xing, Arthur Bucker +13Cross-Embodiment Robot Learning Robotics
Carnegie Mellon University · TU Delft · Lavoro AI +1
Beyond Isolation: A Unified Benchmark for General-Purpose Navigation
May 10, 2026Samson Sun, Tianyi Yang, Tengyue Wang +6Embodied Navigation Cross-Embodiment Robot Learning
1AutoLab, SAI, Shanghai Jiao Tong University · 2Research Lab, Anyverse Dynamics
ReActor: Reinforcement Learning for Physics-Aware Motion Retargeting
May 7, 2026David Müller, Agon Serifi, Sammy Christen +3Cross-Embodiment Robot Learning Motion Retargeting
Disney Research, Switzerland
HumanNet: Scaling Human-centric Video Learning to One Million Hours
May 7, 2026Yufan Deng, Daquan ZhouHuman Activity Recognition Cross-Embodiment Robot Learning
DAGroup · SimpleSilicon Innovation Team Peking University
DexSynRefine: Synthesizing and Refining Human-Object Interaction Motion for Physically Feasible Dexterous Robot Actions
May 7, 2026Hyesung Lee, Hyunwoo Jung, Si-Hwan Heo +1HOI Generation Dexterous Manipulation
Korea Institute of Science and Technology · KAIST · Hanyang University
Bridging the Embodiment Gap: Disentangled Cross-Embodiment Video Editing
May 5, 2026Zhiyuan Li, Wenyan Yang, Wenshuai Zhao +4Disentangled Representation Learning Cross-Embodiment Robot Learning
Department of Electrical Engineering and Automation, Aalto University, Finland · Department of Computer Science, Aalto University, Finland · Hong Kong University of Science and Technology, China +1
Action Agent: Agentic Video Generation Meets Flow-Constrained Diffusion
May 2, 2026Jeffrin Sam, Nguyen Khang, Yara Mahmoud +2Trajectory Generation Diffusion-Based Planning
Intelligent Space Robotics Laboratory, Skoltech, Bolshoy Boulevard, 30, Moscow 121205, Russia
Motubrain: An Advanced World Action Model for Robot Control
Apr 30, 2026Motubrain Team, Chendong Xiang, Fan Bao +17Robotic Control World Models for Robotics
Motubrain Team
Learning Human-Intention Priors from Large-Scale Human Demonstrations for Robotic Manipulation
Apr 27, 2026Yifan Xie, YuAn Wang, Guangyu Chen +3Human Motion Generation Cross-Embodiment Robot Learning
1Tsinghua University · 2ByteDance
BridgeACT: Bridging Human Demonstrations to Robot Actions via Unified Tool-Target Affordances
Apr 25, 2026Yifan Han, Jianxiang Liu, Haoyu Zhang +3Cross-Embodiment Robot Learning Robotic Manipulation
Institute of Automation, Chinese Academy of Sciences. · School of Artificial Intelligence, Shanghai Jiao Tong University. · 3South China University of Technology.
GazeVLA: Learning Human Intention for Robotic Manipulation
Apr 24, 2026Chengyang Li, Kaiyi Xiong, Yuan Xu +3Long-Horizon Robotic Manipulation Robot Skill Learning
Shanghai Jiao Tong University · Peking University · ShanghaiTech University +1

Jun 1, 2026, cs.ROJ/K move · Enter open · S save

SeeTraceAct: Visibility-Aware Latent Planning from Cross-Embodiment Demonstration Videos

Jaehyeon Son, Junhyun Kim, Kyle Kam, Jeremiah Coholich+6

Georgia Institute of Technology · Allen Institute for AI · Johns Hopkins University+1

Robot Skill Learning Generalization in Robotic Manipulation Cross-Embodiment Robot Learning Data-Efficient Robot Learning Learning from Demonstration Vision-Language-Action Models+1

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Vision-language-action models (VLAs) are promising general-purpose robot policies, but adapting them to new tasks typically requires costly task-specific teleoperation data. As an alternative, we study one-shot demo-conditioned VLAs, where a robot policy is conditioned on a single demonstration video of an unseen task. We find that existing end-to-end approaches often struggle when successful execution requires precisely localizing small target regions. To address this limitation, we propose SeeTraceAct, a demo-conditioned VLA framework that encourages precise spatial grounding through visibility-aware prediction of future end-effector traces. To enable reproducible evaluation with cross-embodiment demonstrations, we introduce and release RoboCasa-DC, a demo-conditioned extension of RoboCasa with episode-paired humanoid videos. Experiments on RoboCasa-DC and a real-world benchmark, where a Franka Panda arm is conditioned on human demonstrations, show that SeeTraceAct outperforms baselines, achieving the best success rate across all four RoboCasa-DC settings and improving real-world average success by 12.5 percentage points.

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Latest papers 232