56 citations · 262 across the 66 of their papers we have counts for
25 papers · 1 filter
Feeling the Unexpected: ResTacVLA for Contact-Rich Manipulation via Residual Tactile Representation
Pengwei Zhang, Bin Xie, Xinpan Meng +5
Tactile perception is indispensable for contact-rich manipulation, yet integrating it into Vision-Language-Action (VLA) models often induces modality collapse, where high-bandwidth…
MemoryVLA++: Temporal Modeling via Memory and Imagination in Vision-Language-Action Models
Hao Shi, Weiye Li, Bin Xie +6
Temporal modeling is essential for robotic manipulation, as effective control requires both memory of past interactions and imagination of future states. However, most VLA models r…
QuadVerse: An Integrated Framework Aligning Visual-Physical Reality for Quadruped Simulation
Yuxiang Chen, Yuanhao Wang, Ziheng Zhang +6
Simulation is central to robot learning, yet the sim-to-real gap remains a major bottleneck. Existing approaches often tackle visual or dynamic gaps separately, overlooking how the…
UniLab: A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms
Yufei Jia, Zhanxiang Cao, Mingrui Yu +48
Simulation-based RL for contemporary robot control is increasingly organized around GPU-resident simulation: physics, rollout collection, and learning are placed on a single GPU-ce…
Realtime-VLA FLASH: Speculative Inference Framework for Diffusion-based VLAs
Jiahui Niu, Kefan Gu, Yucheng Zhao +5
Diffusion-based vision-language-action models (dVLAs) are promising for embodied intelligence but are fundamentally limited in real-time deployment by the high latency of full infe…
PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models
Xinyu Guo, Bin Xie, Wei Chai +4
Large-scale pretraining has made Vision-Language-Action (VLA) models promising foundations for generalist robot manipulation, yet adapting them to downstream tasks remains necessar…
GS-Playground: A High-Throughput Photorealistic Simulator for Vision-Informed Robot Learning
Yufei Jia, Heng Zhang, Ziheng Zhang +39
Embodied AI research is undergoing a shift toward vision-centric perceptual paradigms. While massively parallel simulators have catalyzed breakthroughs in proprioception-based loco…
Robotic Scene Cloning:Advancing Zero-Shot Robotic Scene Adaptation in Manipulation via Visual Prompt Editing
Binyuan Huang, Yuqing Wen, Yucheng Zhao +5
Modern robots can perform a wide range of simple tasks and adapt to diverse scenarios in the well-trained environment. However, deploying pre-trained robot models in real-world use…
DM0: An Embodied-Native Vision-Language-Action Model towards Physical AI
En Yu, Haoran Lv, Jianjian Sun +46
Moving beyond the traditional paradigm of adapting internet-pretrained models to physical tasks, we present DM0, an Embodied-Native Vision-Language-Action (VLA) framework designed…
SpatialActor: Exploring Disentangled Spatial Representations for Robust Robotic Manipulation
Hao Shi, Bin Xie, Yingfei Liu +5
Robotic manipulation requires precise spatial understanding to interact with objects in the real world. Point-based methods suffer from sparse sampling, leading to the loss of fine…
Running VLAs at Real-time Speed
Yunchao Ma, Yizhuang Zhou, Yunhuan Yang +2
In this paper, we show how to run pi0-level multi-view VLA at 30Hz frame rate and at most 480Hz trajectory frequency using a single consumer GPU. This enables dynamic and real-time…
Dexbotic: Open-Source Vision-Language-Action Toolbox
Bin Xie, Erjin Zhou, Fan Jia +36
In this paper, we present Dexbotic, an open-source Vision-Language-Action (VLA) model toolbox based on PyTorch. It aims to provide a one-stop VLA research service for professionals…
ManiAgent: An Agentic Framework for General Robotic Manipulation
Yi Yang, Kefan Gu, Yuqing Wen +4
While Vision-Language-Action (VLA) models have demonstrated impressive capabilities in robotic manipulation, their performance in complex reasoning and long-horizon task planning i…
IntentionVLA: Generalizable and Efficient Embodied Intention Reasoning for Human-Robot Interaction
Yandu Chen, Kefan Gu, Yuqing Wen +3
Vision-Language-Action (VLA) models leverage pretrained vision-language models (VLMs) to couple perception with robotic control, offering a promising path toward general-purpose em…
MUVLA: Learning to Explore Object Navigation via Map Understanding
Peilong Han, Fan Jia, Min Zhang +5
In this paper, we present MUVLA, a Map Understanding Vision-Language-Action model tailored for object navigation. It leverages semantic map abstractions to unify and structure hist…
LLaDA-VLA: Vision Language Diffusion Action Models
Yuqing Wen, Hebei Li, Kefan Gu +3
The rapid progress of auto-regressive vision-language models (VLMs) has inspired growing interest in vision-language-action models (VLA) for robotic manipulation. Recently, masked…
GeoVLA: Empowering 3D Representations in Vision-Language-Action Models
Lin Sun, Bin Xie, Yingfei Liu +3
Vision-Language-Action (VLA) models have emerged as a promising approach for enabling robots to follow language instructions and predict corresponding actions. However, current VLA…
MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation
Hao Shi, Bin Xie, Yingfei Liu +7
Temporal context is essential for robotic manipulation because such tasks are inherently non-Markovian, yet mainstream VLA models typically overlook it and struggle with long-horiz…
ROSA: Harnessing Robot States for Vision-Language and Action Alignment
Yuqing Wen, Kefan Gu, Haoxuan Liu +4
Vision-Language-Action (VLA) models have recently made significant advance in multi-task, end-to-end robotic control, due to the strong generalization capabilities of Vision-Langua…
Glad: A Streaming Scene Generator for Autonomous Driving
Bin Xie, Yingfei Liu, Tiancai Wang +2
The generation and simulation of diverse real-world scenes have significant application value in the field of autonomous driving, especially for the corner cases. Recently, researc…
BFA: Best-Feature-Aware Fusion for Multi-View Fine-grained Manipulation
Zihan Lan, Weixin Mao, Haosheng Li +4
In real-world scenarios, multi-view cameras are typically employed for fine-grained manipulation tasks. Existing approaches (e.g., ACT) tend to treat multi-view features equally an…
Multi-GraspLLM: A Multimodal LLM for Multi-Hand Semantic Guided Grasp Generation
Haosheng Li, Weixin Mao, Weipeng Deng +7
Multi-hand semantic grasp generation aims to generate feasible and semantically appropriate grasp poses for different robotic hands based on natural language instructions. Although…
RoboMatrix: A Skill-centric Hierarchical Framework for Scalable Robot Task Planning and Execution in Open-World
Weixin Mao, Weiheng Zhong, Zhou Jiang +8
Existing robot policies predominantly adopt the task-centric approach, requiring end-to-end task data collection. This results in limited generalization to new tasks and difficulti…
RoboGSim: A Real2Sim2Real Robotic Gaussian Splatting Simulator
Xinhai Li, Jialin Li, Ziheng Zhang +6
Efficient acquisition of real-world embodied data has been increasingly critical. However, large-scale demonstrations captured by remote operation tend to take extremely high costs…