3 citations · 5 across the 22 of their papers we have counts for
29 papers
WorldMirror: Agentic Real-to-Sim Generation of Interactive Worlds from In-the-Wild Robot Demonstrations
Tianling Xu, Weijie Wan, Honghao Su +9
Existing approaches for robot learning in simulation often require substantial manual effort to construct scenes and specify tasks, limiting training scalability and data diversity…
Spark-0: Scaling Spatially Aligned Tactile Pretraining for Robot Dexterous Manipulation
Tianxing Chen, Wenwei Lin, Chuqiao Lyu +19
Generalist robot policies benefit from large-scale visual pretraining but often struggle with contact-rich dexterous manipulation, where force, compliance, and incipient slip are h…
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
Qize Yu, Lianrui Fan, Boyu Chen +23
Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tiny objects, and it has to be fast enough for closed-loop cont…
Beyond Future Prediction: Denoising as Generative Adaptation for Robot Control
Zanyi Wang, Yuheng Lei, Dengyang Jiang +4
Pretrained generative Diffusion Transformers (DiTs) capture rich pixel-level visual and language-conditioned structure through large-scale image and video generation training. A gr…
DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation
Yan Qin, Yue Chen, Wenwei Lin +9
Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots and remain tied to embodiment…
MoPA: Coordinated Mobile Manipulation via Subsystem-Specific Perception Alignment
Guangyu Chen, Qiwei Liang, Shaolong Zhu +7
Mobile manipulation requires perceptual evidence at different spatial scales for base motion and arm control, while the two action modalities remain kinematically coupled. Existing…
Assembling Two Parts in One Hand
Liuao Pei, Tianyue Wu, Hui Zhang +2
A hallmark of human dexterity is the cooperative use of fingers, where different fingers take on distinct yet coordinated roles to accomplish fine manipu- lation, such as capping a…
XPolicyLab: A Unified Standard and Open Ecosystem for Robot Policy Evaluation and Deployment
XPolicyLab Community, Tianxing Chen, Yue Chen +67
Robot policy evaluation and deployment remain fragmented by model-specific software dependencies, data representations, and runtime interfaces, so that connecting N policies to M e…
SoftVTBench: A Deformation-Aware Visuo-Tactile Dataset and Benchmark for Deformable-Object Manipulation
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Physical interaction quality is central to deformable-object manipulation, yet most benchmarks evaluate task success alone. A policy may complete the task while allowing slip or ca…
SoftVTBench: A Safety-Aware Visuo-Tactile Benchmark for Physically Constrained Robotic Manipulation of Deformable Objects (Early Version)
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Deformable object manipulation poses challenges beyond task completion: successful execution must also maintain safe physical interaction, holding the object stably without slip or…
Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels
Xinyu Yang, Tianxing Chen, Honghao Su +38
Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction. Because failures can cause immediate physical…
RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies
Tianxing Chen, Yue Chen, Zixuan Li +41
Generalist robot manipulation policies have advanced rapidly, yet existing benchmarks remain limited in systematically evaluating their capabilities. Many rely on simple, short-hor…
Planning-aligned Token Compression for Long-Context Autonomous Driving
Zhixuan Liang, Yuxiao Chen, Yurong You +12
Monolithic vision-action models represent an emerging paradigm in autonomous driving. However, this architecture produces token sequences that quickly exceed real-time computationa…
AttenA+: Rectifying Action Inequality in Robotic Foundation Models
Daojie Peng, Fulong Ma, Jiahang Cao +7
Existing robotic foundation models, while powerful, are predicated on an implicit assumption of temporal homogeneity: treating all actions as equally informative during optimizatio…
HyperSim: A Holistic Sim-To-Real Framework For Robust Robotic Manipulation
Junyi Dong, Haotian Luo, Ziwei Xu +11
Scaling data volume and diversity is critical for generalizing embodied intelligence. While synthetic data generation offers a scalable alternative to expensive physical data acqui…
Unveiling High-Probability Generalization in Decentralized SGD
Jiahuan Wang, Ping Luo, Ziqing Wen +2
Decentralized stochastic gradient descent (D-SGD) is an efficient method for large-scale distributed learning. Existing generalization studies mainly address expected results, achi…
HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System
Tianshuo Yang, Guanyu Chen, Yutian Chen +8
While end-to-end Vision-Language-Action (VLA) models offer a promising paradigm for robotic manipulation, fine-tuning them on narrow control data often compromises the profound rea…
ManiTwin: Scaling Data-Generation-Ready Digital Object Dataset to 100K
Kaixuan Wang, Tianxing Chen, Jiawei Liu +13
Learning in simulation provides a useful foundation for scaling robotic manipulation capabilities. However, this paradigm often suffers from a lack of data-generation-ready digital…
VPWEM: Non-Markovian Visuomotor Policy with Working and Episodic Memory
Yuheng Lei, Zhixuan Liang, Hongyuan Zhang +1
Imitation learning from human demonstrations has achieved significant success in robotic control, yet most visuomotor policies still condition on single-step observations or short-…
Performance-guided Reinforced Active Learning for Object Detection
Zhixuan Liang, Xingyu Zeng, Rui Zhao +1
Active learning (AL) strategies aim to train high-performance models with minimal labeling efforts, only selecting the most informative instances for annotation. Current approaches…
Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
Zhixuan Liang, Yizhuo Li, Tianshuo Yang +9
Vision-Language-Action (VLA) models adapt large vision-language backbones to map images and instructions into robot actions. However, prevailing VLAs either generate actions autore…
Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop
Tianxing Chen, Kaixuan Wang, Zhaohui Yang +96
Embodied Artificial Intelligence (Embodied AI) is an emerging frontier in robotics, driven by the need for autonomous systems that can perceive, reason, and act in complex physical…
RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
Tianxing Chen, Zanxin Chen, Baijun Chen +23
Simulation-based data synthesis has emerged as a powerful paradigm for advancing real-world robotic manipulation. Yet existing datasets remain insufficient for robust bimanual mani…
RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins
Yao Mu, Tianxing Chen, Zanxin Chen +11
In the rapidly advancing field of robotics, dual-arm coordination and complex object manipulation are essential capabilities for developing advanced autonomous systems. However, th…