6 citations · 11 across the 29 of their papers we have counts for
31 papers
Discrete Forcing: Infusing Discrete Guidance into Continuous Denoising for Few-Step Action Experts
Jingbo Wang, Wenxuan Song, Wenhao Yu +6
Efficient action generation in vision-language-action (VLA) models requires capturing both coarse action structure and fine-grained details. Discrete action tokens provide compact…
Xiaomi-Robotics-1: Scaling Vision-Language-Action Models with over 100K Hours of Real-World Trajectories
Xiaomi Robotics Team, Jun Guo, Piaopiao Jin +31
We present Xiaomi-Robotics-1, a foundational vision-language-action (VLA) model capable of (1) following diverse language instructions to perform a wide range of mobile manipulatio…
Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model
Xinghang Li, Jun Guo, Qiwei Li +21
Recent foundation image and video generation models offer strong generalization and controllability, but their direct application to embodied scenarios is limited by requirements f…
RoboMemArena: A Comprehensive and Challenging Robotic Memory Benchmark
Huashuo Lei, Wenxuan Song, Huarui Zhang +10
Memory is a critical component of robotic intelligence, as robots must rely on past observations and actions to accomplish long-horizon tasks in partially observable environments.…
CapVector: Learning Transferable Capability Vectors in Parametric Space for Vision-Language-Action Models
Wenxuan Song, Han Zhao, Fuhao Li +7
This paper proposes a novel approach to address the challenge that pretrained VLA models often fail to effectively improve performance and reduce adaptation costs during standard s…
VAMPO: Policy Optimization for Improving Visual Dynamics in Video Action Models
Zirui Ge, Pengxiang Ding, Baohua Yin +16
Video action models are an appealing foundation for Vision--Language--Action systems because they can learn visual dynamics from large-scale video data and transfer this knowledge…
FRAPPE: Infusing World Modeling into Generalist Policies via Multiple Future Representation Alignment
Han Zhao, Jingbo Wang, Wenxuan Song +5
Enabling VLA models to predict environmental dynamics, known as world modeling, has been recognized as essential for improving robotic reasoning and generalization. However, curren…
CRL-VLA: Continual Vision-Language-Action Learning
Qixin Zeng, Shuo Zhang, Hongyin Zhang +6
Lifelong learning is critical for embodied agents in open-world environments, where reinforcement learning fine-tuning has emerged as an important paradigm to enable Vision-Languag…
BabyVision: Visual Reasoning Beyond Language
Liang Chen, Weichu Xie, Yiyan Liang +27
While humans develop core visual skills long before acquiring language, contemporary Multimodal LLMs (MLLMs) still rely heavily on linguistic priors to compensate for their fragile…
Embodied Robot Manipulation in the Era of Foundation Models: Planning and Learning Perspectives
Shuanghao Bai, Wenxuan Song, Jiayi Chen +14
Recent advances in vision, language, and multimodal learning have significantly accelerated progress in robotic foundation models, with robotic manipulation remaining one of the mo…
Unified Diffusion VLA: Vision-Language-Action Model via Joint Discrete Denoising Diffusion Process
Jiayi Chen, Wenxuan Song, Pengxiang Ding +5
Vision-language-action (VLA) models aim to understand natural language instructions and visual observations and to execute corresponding actions as an embodied agent. Recent work i…
Spatial Forcing: Implicit Spatial Representation Alignment for Vision-language-action Model
Fuhao Li, Wenxuan Song, Han Zhao +5
Vision-language-action (VLA) models have recently shown strong potential in enabling robots to follow language instructions and execute precise actions. However, most VLAs are buil…
VLA^2: Empowering Vision-Language-Action Models with an Agentic Framework for Unseen Concept Manipulation
Han Zhao, Jiaxuan Zhang, Wenxuan Song +2
Current vision-language-action (VLA) models, pre-trained on large-scale robotic data, exhibit strong multi-task capabilities and generalize well to variations in visual and languag…
Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey
Shuanghao Bai, Wenxuan Song, Jiayi Chen +15
Embodied intelligence has witnessed remarkable progress in recent years, driven by advances in computer vision, natural language processing, and the rise of large-scale multimodal…
VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
Yihao Wang, Pengxiang Ding, Lingxiao Li +13
Vision-Language-Action (VLA) models typically bridge the gap between perceptual and action spaces by pre-training a large-scale Vision-Language Model (VLM) on robotic data. While t…
ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver
Wenxuan Song, Ziyang Zhou, Han Zhao +7
Recent advances in Vision-Language-Action (VLA) models have enabled robotic agents to integrate multimodal understanding with action execution. However, our empirical analysis reve…
CEED-VLA: Consistency Vision-Language-Action Model with Early-Exit Decoding
Wenxuan Song, Jiayi Chen, Pengxiang Ding +4
In recent years, Vision-Language-Action (VLA) models have become a vital research direction in robotics due to their impressive multimodal understanding and generalization capabili…
RationalVLA: A Rational Vision-Language-Action Model with Dual System
Wenxuan Song, Jiayi Chen, Wenxue Li +12
A fundamental requirement for real-world robotic deployment is the ability to understand and respond to natural language instructions. Existing language-conditioned manipulation ta…
Unveiling the Potential of Vision-Language-Action Models with Open-Ended Multimodal Instructions
Wei Zhao, Gongsheng Li, Zhefei Gong +3
Vision-Language-Action (VLA) models have recently become highly prominent in the field of robotics. Leveraging vision-language foundation models trained on large-scale internet dat…
ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning
Hongyin Zhang, Zifeng Zhuang, Han Zhao +3
Vision-Language-Action (VLA) models have shown great potential in general robotic decision-making tasks via imitation learning. However, the variable quality of training data often…
OpenHelix: A Short Survey, Empirical Analysis, and Open-Source Dual-System VLA Model for Robotic Manipulation
Can Cui, Pengxiang Ding, Wenxuan Song +10
Dual-system VLA (Vision-Language-Action) architectures have become a hot topic in embodied intelligence research, but there is a lack of sufficient open-source work for further per…
SSR: Enhancing Depth Perception in Vision-Language Models via Rationale-Guided Spatial Reasoning
Yang Liu, Ming Ma, Xiaomin Yu +5
Despite impressive advancements in Visual-Language Models (VLMs) for multi-modal tasks, their reliance on RGB inputs limits precise spatial understanding. Existing methods for inte…
MoRE: Unlocking Scalability in Reinforcement Learning for Quadruped Vision-Language-Action Models
Han Zhao, Wenxuan Song, Donglin Wang +4
Developing versatile quadruped robots that can smoothly perform various actions and tasks in real-world environments remains a significant challenge. This paper introduces a novel…
PD-VLA: Accelerating Vision-Language-Action Model Integrated with Action Chunking via Parallel Decoding
Wenxuan Song, Jiayi Chen, Pengxiang Ding +9
Vision-Language-Action (VLA) models demonstrate remarkable potential for generalizable robotic manipulation. The performance of VLA models can be improved by integrating with actio…