1 citations · 2 across the 16 of their papers we have counts for
17 papers
HEFT: Heavy-Payload Full-size Humanoid Teleoperation with Privileged Motion Guidance and Windowed Payload Curriculum
Chenxin Liu, Qingzhou Lu, Guangxiao Yang +4
General motion tracking and teleoperation offer a promising path to scalable humanoid skill acquisition, yet most existing frameworks are validated on compact platforms or without…
UAM: A Dual-Stream Perspective on Forgetting in VLA Training
Jianke Zhang, Yuanfei Luo, Yucheng Hu +6
Vision--language--action (VLA) models are typically built by fine-tuning a pretrained vision--language model (VLM) on action data. However, we show that this standard recipe system…
Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training
Yaxuan Li, Zhongyi Zhou, Yefei Chen +5
Post-training is essential for turning pretrained generalist robot policies into reliable task-specific controllers, but existing human-in-the-loop pipelines remain tied to physica…
Veo-Act: Enhancing VLA Policies with Frontier Video Models
Zhongru Zhang, Chenghan Yang, Qingzhou Lu +4
Video generation models can produce coherent vi- sual sequences depicting object motion and interactions. We in- vestigate how frontier video generation models can complement visio…
Learning Additively Compositional Latent Actions for Embodied AI
Hangxing Wei, Xiaoyu Chen, Chuheng Zhang +5
Latent action learning infers pseudo-action labels from visual transitions, providing an approach to leverage internet-scale video for embodied AI. However, most methods learn late…
VLAW: Iterative Co-Improvement of Vision-Language-Action Policy and World Model
Yanjiang Guo, Tony Lee, Lucy Xiaoyang Shi +3
The goal of this paper is to improve the performance and reliability of vision-language-action (VLA) models through iterative online interaction. Since collecting policy rollouts i…
BagelVLA: Enhancing Long-Horizon Manipulation via Interleaved Vision-Language-Action Generation
Yucheng Hu, Jianke Zhang, Yuanfei Luo +9
Equipping embodied agents with the ability to reason about tasks, foresee physical outcomes, and generate precise actions is essential for general-purpose manipulation. While recen…
VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models
Jianke Zhang, Xiaoyu Chen, Qiuyue Wang +7
Vision-Language-Action (VLA) models, which integrate pretrained large Vision-Language Models (VLM) into their policy backbone, are gaining significant attention for their promising…
UniJEPA: Enhancing Robot Policy via Unified Continuous and Discrete Representation Learning
Jianke Zhang, Yucheng Hu, Yanjiang Guo +5
Building generalist robot policies that can handle diverse tasks in open-ended environments is a central challenge in robotics. To leverage knowledge from large-scale pretraining,…
Ctrl-World: A Controllable Generative World Model for Robot Manipulation
Yanjiang Guo, Lucy Xiaoyang Shi, Jianyu Chen +1
Generalist robot policies can now perform a wide range of manipulation skills, but evaluating and improving their ability with unfamiliar objects and instructions remains a signifi…
villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models
Xiaoyu Chen, Hangxing Wei, Pushi Zhang +9
Vision-Language-Action (VLA) models have emerged as a popular paradigm for learning robot manipulation policies that can follow language instructions and generalize to novel scenar…
Improving Vision-Language-Action Model with Online Reinforcement Learning
Yanjiang Guo, Jianke Zhang, Xiaoyu Chen +4
Recent studies have successfully integrated large vision-language models (VLMs) into low-level robotic control by supervised fine-tuning (SFT) with expert robotic datasets, resulti…
UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent
Jianke Zhang, Yanjiang Guo, Yucheng Hu +3
Recent advancements in Vision-Language-Action (VLA) models have leveraged pre-trained Vision-Language Models (VLMs) to improve the generalization capabilities. VLMs, typically pre-…
Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations
Yucheng Hu, Yanjiang Guo, Pengchao Wang +6
Visual representations play a crucial role in developing generalist robotic policies. Previous vision encoders, typically pre-trained with single-image reconstruction or two-image…
Prediction with Action: Visual Policy Learning via Joint Denoising Process
Yanjiang Guo, Yucheng Hu, Jianke Zhang +4
Diffusion models have demonstrated remarkable capabilities in image generation tasks, including image editing and video creation, representing a good understanding of the physical…
HiRT: Enhancing Robotic Control with Hierarchical Robot Transformers
Jianke Zhang, Yanjiang Guo, Xiaoyu Chen +4
Large Vision-Language-Action (VLA) models, leveraging powerful pre trained Vision-Language Models (VLMs) backends, have shown promise in robotic control due to their impressive gen…
Efficient and Generalized end-to-end Autonomous Driving System with Latent Deep Reinforcement Learning and Demonstrations
Zuojin Tang, Xiaoyu Chen, Yongqiang Li +1
An intelligent driving system should dynamically formulate appropriate driving strategies based on the current environment and vehicle status while ensuring system security and rel…