Generalization in Robotic Manipulation

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Zeva: In-Context Causal Learning for Generalizable Embodied Manipulation
Aug 31, 2026Fu Chen, Xin Ding, Bingjia Huang +8Robot Policy Learning ICL for Robotics
Institute for AI Industry Research (AIR), Tsinghua University
Teach and Grow: An Agent-Centered Architecture for General Robot Learning
Aug 17, 2026Chang Nie, Zhe Liu, Hesheng WangRobot Skill Learning Generalization in Robotic Manipulation
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, and the Shanghai Key Laboratory of Navigation and Location Based Services, Shanghai 200240, China
RoboSynChallenge: Mastering Real-World Dexterity via Generalizing Synthesized Manipulation Skills
Aug 12, 2026Runyi Zhao, Ruixin Wu, Chengkun Li +15Sim-to-Real Transfer Generalization in Robotic Manipulation
Shenzhen Loop Area Institute (SLAI) · The Chinese University of Hong Kong, Shenzhen · DexForce +8
AdaDexGrasp: Adaptive Dexterous Grasping via 3D Visuo-Tactile Representation Fusion
Aug 6, 2026Xirui Liang, Jiaqi Liang, Jingkai Xu +6Robotic Grasping Visuo-Tactile Representation Learning
Peking University, Beijing, China · The Hong Kong University of Science and Technology, Hong Kong, China · University of California, Berkeley, CA, USA
SkillMemo: Expert-guided Skill Memory Framework for Compositional Embodied Manipulation
Aug 6, 2026Changyuan Wang, Chubin Zhang, Zhenyu Wu +8Long-Horizon Robotic Manipulation Robot Skill Learning
Shenzhen International Graduate School, Tsinghua University · Department of Automation, Tsinghua University · Nanyang Technological University +1
ARGUS: Aligning Robot Scene Geometry Under Shifting Views with Large 3D Vision Models
Aug 6, 2026Rishik Sathua, Haonan Chen, Katherine Driggs-CampbellGeneralization in Robotic Manipulation Visuomotor Policy Learning
University of Illinois at Urbana-Champaign · Harvard University
BridgeVLA++: A Data-Efficient, Generalizable, and Memory-Augmented Vision-Language-Action Framework for 3D Manipulation
Aug 5, 2026Peiyan Li, Yuze Zhu, Yixiang Chen +10Memory-Augmented VLMs Generalization in Robotic Manipulation
New Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China · FiveAges, Beijing, China +1
Faster-WAM: Efficient Inference-Time Future Conditioning for Robust World Action Models
Aug 5, 2026Weiheng Zhao, Haoyi Jiang, Xin Shi +5Action-Conditioned World Models Efficient VLA Model Inference
Huazhong University of Science and Technology · D-Robotics · Horizon Robotics +1
RoboReact: Agentic Skill Distillation from Generated Egocentric Videos for Generalizable Whole-Body Manipulation
Aug 4, 2026Shuliang He, Shuai Wang, Bo Yue +3Robot Skill Learning Generalization in Robotic Manipulation
The Chinese University of Hong Kong, Shenzhen · JD Technology · Tsinghua University
Ego2Robot: Scalable Robot Data Synthesis from Egocentric Human Data
Aug 3, 2026Ye Wang, Pei Lin, Xiong-Hui Chen +12Robot Skill Learning Generalization in Robotic Manipulation
1AIM3 Lab, Renmin University of China · 2Qwen Team, Alibaba Inc. · 3ShanghaiTech University +2
AffordTrajDP: Dynamic Affordance-Guided Visuomotor Policy Learning for Robotic Manipulation
Aug 3, 2026Gaoyuan Wu, Ziyu Shan, Haoyang Du +2Robot Skill Learning Generalization in Robotic Manipulation
1Nanyang Technological University, Singapore
Sparse Meets Dense: Correspondence Guided Robotic Manipulation with Rigid-Deformable Interactions
Aug 2, 2026Ziyu Zhu, Yue Chen, Xirui Liang +5Deformable Object Manipulation Generalization in Robotic Manipulation
School of EECS, PKU · CFCS, School of Computer Science, PKU
OC-VLA++: Monocular Geometry-Guided Cross-View Consistency for Viewpoint-Robust Robotic Manipulation
Aug 2, 2026Tianyi Zhang, Ziyang Gong, Zhenjie Yang +2Multi-View Consistency Generalization in Robotic Manipulation
Zhejiang University · Shanghai Jiao Tong University · The University of Hong Kong +2
Diagnosing Compositional Generalization in Sequential Robot Tasks
Jul 31, 2026Yixiao Wang, Cheng-En Wu, Lingfeng Sun +5Language-Conditioned Robot Manipulation Robotic Data Collection
University of California, Berkeley · Tsinghua University
ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts
Jul 31, 2026Mingxin Wang, Bin Hu, Bin Qian +12World Models for Robotics Generalization in Robotic Manipulation
1Tsinghua University · 2AMAP-CV-LAB, Alibaba Group · 3Shanghai Jiao Tong University +3
SemAnCorr: Semantic Anchored Correspondence for Zero-Shot Manipulation Skill Transfer
Jul 30, 2026Xiaoxiang Dong, William Baron, Hongyi Chen +3Semantic Correspondence Zero-Shot Robotic Manipulation
Robotics Institute, Carnegie Mellon University, USA. · College of Connected Computing, Vanderbilt University, USA. · College of Engineering, University of California, Berkeley, USA. +1
UniCross: Unified Cross-Skill Dexterous Manipulation Synthesis
Jul 30, 2026Hui Zhang, Julian Ferchow, Jie Song +1Robotic Grasping Dexterous Manipulation
ETH Zürich, Switzerland · inspire AG, Zürich, Switzerland · HKUST (Guangzhou), China
MoMo: Dial Motion Mode in Robot Manipulation with Spatiotemporal Action Tokenization
Jul 28, 2026Yuhan Hu, Hugues Thomas, Peide Huang +3Robot Skill Learning Generalization in Robotic Manipulation
Apple
Decompose and Reorganize: Planning with Primitives and Visuomotor Policies Learned from Demonstrations
Jul 28, 2026Yizhou Chen, Hang Xu, Dongjie Yu +7Long-Horizon Robotic Manipulation Robot Skill Learning
The University of Hong Kong, Hong Kong · JD.com (JingDong) · Nanyang Technological University (NTU), Singapore +3
KAI: A Kinematic-Aware Interface for Data-Efficient Articulated Object Manipulation
Jul 27, 2026Yaping Li, Zhaxizhuoma, Qiaojun Yu +3Robot Skill Learning Generalization in Robotic Manipulation
The Chinese University of Hong Kong · Shanghai AI Laboratory · Shanghai Jiao Tong University
FloAff-Kitchen: Bridging Navigation and Manipulation via Canonical and Progressive Floor Affordance Learning
Jul 27, 2026Ping Zhong, Manling Teng, Tao Wu +3Mobile Manipulation Generalization in Robotic Manipulation
School of Computer Science and Engineering, Central South University
One Hand Watches The Other: Dynamic Multi-Agent Cooperation for Sample-Efficient Bimanual Manipulation in Dynamic Environments
Jul 24, 2026Jan Ole von Hartz, Abhinav Valada, Joschka BoedeckerBimanual Robotic Manipulation Generalization in Robotic Manipulation
Department of Computer Science, University of Freiburg, Germany.
Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation
Jul 23, 2026Yu Qi, Zhang Ye, Xinyi Xu +6Robot Skill Learning Language-Conditioned Robot Manipulation
Northeastern University · NVIDIA
GuidedAttention: Interpretable and Correctable Visual Attention for OOD-Robust Robot Manipulation via Imitation Learning
Jul 23, 2026Masaki Murooka, Ryoichi Nakajo, Keisuke Shirai +4Visual Attention Robot Skill Learning
CNRS-AIST JRL (Joint Robotics Laboratory), IRL, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8560, Japan · Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan
TableVerse: A Large-scale Tabletop Dataset with Real-world Grounded Layouts for Generalizable Manipulation
Jul 23, 2026Boyuan Wang, Yue Zhang, Xutao Xue +2Robotic Data Collection Robotics Simulation
ByteDance
Dynamics-Aware Meta-Imitation for Generalization to Unseen Robotic Manipulation
Jul 17, 2026Zhenduo Shang, Xiyao Liu, Bohan Li +4Robot Skill Learning Generalization in Robotic Manipulation
State Key Laboratory of Robotics and Intelligent Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China · University of Chinese Academy of Sciences, Beijing 100049, China · Shenyang University of Technology
AC-VLA: Robust Out-of-Distribution Action Execution via Compositional Learning
Jul 17, 2026Xiaojiang Peng, Kai Peng, Jie Lu +3Robot Skill Learning Generalization in Robotic Manipulation
Shenzhen Technology University · Tongji University · Great Bay University +1
Semantic Anchoring for Robotic Action Representations
Jul 15, 2026Yuan Xu, Youheng Shi, Chengyang Li +2Generalization in Robotic Manipulation Vision-Language-Action Models
Peking University · Eastern Institute of Technology, Ningbo · Shanghai Jiao Tong University
Worlds in One Demo: A Synthetic Data Engine for Learning Open-World Mobile Manipulation
Jul 14, 2026Lingxiao Guo, Huanyu Li, Guanya ShiLong-Horizon Robotic Manipulation Mobile Manipulation
Carnegie Mellon University
GraspGraphNet: Graph-Structured Multi-Embodiment Dexterous Grasp Generation
Jul 13, 2026Yeonseo Lee, Taeyeop Lee, Hyosup Shin +2Robotic Grasping Graph Neural Networks
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea.

Aug 31, 2026, cs.ROJ/K move · Enter open · S save

Zeva: In-Context Causal Learning for Generalizable Embodied Manipulation

Fu Chen, Xin Ding, Bingjia Huang, Xiangyu Li+7

Institute for AI Industry Research (AIR), Tsinghua University

Robot Policy Learning ICL for Robotics Robot Skill Learning Generalization in Robotic Manipulation Robotic Manipulation Robot Learning

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Generalizable embodied manipulation remains difficult to achieve through pretraining alone, due to unseen physical conditions in the real world. We argue that robots need to learn from their own physical interactions on the fly during real-world deployment and use this knowledge to inform subsequent actions. We present Zeva, the first framework that enables in-context learning from a robot's own physical interaction experience while keeping the policy model frozen. Zeva employs a Causal Interaction Extractor to encode an executed action and its induced state change into a causal interaction signal, which is stored in a dual-timescale causal memory. For subsequent actions, relevant causal interaction signals are retrieved from memory and injected into the frozen policy model as context. Experiments in simulation and real-world manipulation demonstrate that Zeva achieves the best performance among the compared frontier VLAs and WAMs and, more importantly, enables self-evolution during deployment without gradient updates. Its success rate continues to improve as the robot accumulates interaction experience. Furthermore, the acquired interaction experience can generalize across tasks.

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