9 citations · 10 across the 12 of their papers we have counts for
13 papers
VLA-Precision: Asymmetric Co-Bootstrapping for Efficient Real-World Online RL of Vision-Language-Action Models
Chenyu Su, Zhaolong Shen, Yuan Qian +8
Pretrained vision-language-action (VLA) models enable broad manipulation but remain unreliable in tasks demanding precision and repeatability. Applying real-world online reinforcem…
SkiP: When to Skip and When to Refine for Efficient Robot Manipulation
Mingtong Dai, Guanqi Peng, Yongjie Bai +5
Previous imitation learning policies predict future actions at every control step, whether in smooth motion phases or precise, contact-rich operation phases. This uniform treatment…
CF-VLA: Efficient Coarse-to-Fine Action Generation for Vision-Language-Action Policies
Fan Du, Feng Yan, Jianxiong Wu +8
Flow-based vision-language-action (VLA) policies offer strong expressivity for action generation, but suffer from a fundamental inefficiency: multi-step inference is required to re…
RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case
Baihui Xiao, Chengjian Feng, Zhijian Huang +3
Collecting real-world data for rare high-risk scenarios, long-tailed driving events, and complex interactions remains challenging, leading to poor performance of existing autonomou…
TopoDiT-3D: Topology-Aware Diffusion Transformer with Bottleneck Structure for 3D Point Cloud Generation
Zechao Guan, Feng Yan, Shuai Du +2
Recent advancements in Diffusion Transformer (DiT) models have significantly improved 3D point cloud generation. However, existing methods primarily focus on local feature extracti…
InstructVEdit: A Holistic Approach for Instructional Video Editing
Chi Zhang, Chengjian Feng, Feng Yan +5
Video editing according to instructions is a highly challenging task due to the difficulty in collecting large-scale, high-quality edited video pair data. This scarcity not only li…
Boosting Robotic Manipulation Generalization with Minimal Costly Data
Liming Zheng, Feng Yan, Fanfan Liu +3
The growing adoption of Vision-Language-Action (VLA) models in embodied AI intensifies the demand for diverse manipulation demonstrations. However, high costs associated with data…
RoboTron-Nav: A Unified Framework for Embodied Navigation Integrating Perception, Planning, and Prediction
Yufeng Zhong, Chengjian Feng, Feng Yan +3
In language-guided visual navigation, agents locate target objects in unseen environments using natural language instructions. For reliable navigation in unfamiliar scenes, agents…
RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving
Zhijian Huang, Chengjian Feng, Feng Yan +5
Large Multimodal Models (LMMs) have demonstrated exceptional comprehension and interpretation capabilities in Autonomous Driving (AD) by incorporating large language models. Despit…
RoboTron-Mani: All-in-One Multimodal Large Model for Robotic Manipulation
Feng Yan, Fanfan Liu, Liming Zheng +5
Recently, robotics has advanced significantly through the integration of larger models and large-scale datasets. However, challenges remain in applying these models to 3D spatial i…
RoboCAS: A Benchmark for Robotic Manipulation in Complex Object Arrangement Scenarios
Liming Zheng, Feng Yan, Fanfan Liu +3
Foundation models hold significant potential for enabling robots to perform long-horizon general manipulation tasks. However, the simplicity of tasks and the uniformity of environm…
DaDu-Corki: Algorithm-Architecture Co-Design for Embodied AI-powered Robotic Manipulation
Yiyang Huang, Yuhui Hao, Bo Yu +8
Embodied AI robots have the potential to fundamentally improve the way human beings live and manufacture. Continued progress in the burgeoning field of using large language models…
RoboUniView: Visual-Language Model with Unified View Representation for Robotic Manipulation
Fanfan Liu, Feng Yan, Liming Zheng +3
Utilizing Vision-Language Models (VLMs) for robotic manipulation represents a novel paradigm, aiming to enhance the model's ability to generalize to new objects and instructions. H…