3 citations · 8 across the 13 of their papers we have counts for
13 papers
Embodiment Transfer Learning for Vision-Language-Action Models
Chengmeng Li, Yaxin Peng
Vision-language-action (VLA) models have significantly advanced robotic learning, enabling training on large-scale, cross-embodiment data and fine-tuning for specific robots. Howev…
ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration
Minjie Zhu, Yichen Zhu, Jinming Li +6
Imitation learning has proven to be highly effective in teaching robots dexterous manipulation skills. However, it typically relies on large amounts of human demonstration data, wh…
ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model
Zhongyi Zhou, Yichen Zhu, Minjie Zhu +8
Humans possess a unified cognitive ability to perceive, comprehend, and interact with the physical world. Why can't large language models replicate this holistic understanding? Thr…
Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning
Zhongyi Zhou, Yaxin Peng, Pin Yi +2
Continual Learning enables models to learn and adapt to new tasks while retaining prior knowledge. Introducing new tasks, however, can naturally lead to feature entanglement across…
Efficient Feature Fusion for UAV Object Detection
Xudong Wang, Yaxin Peng, Chaomin Shen
Object detection in unmanned aerial vehicle (UAV) remote sensing images poses significant challenges due to unstable image quality, small object sizes, complex backgrounds, and env…
Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning
Junjie Wen, Minjie Zhu, Yichen Zhu +8
In this paper, we present DiffusionVLA, a novel framework that seamlessly combines the autoregression model with the diffusion model for learning visuomotor policy. Central to our…
Scaling Diffusion Policy in Transformer to 1 Billion Parameters for Robotic Manipulation
Minjie Zhu, Yichen Zhu, Jinming Li +8
Diffusion Policy is a powerful technique tool for learning end-to-end visuomotor robot control. It is expected that Diffusion Policy possesses scalability, a key attribute for deep…
TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation
Junjie Wen, Yichen Zhu, Jinming Li +9
Vision-Language-Action (VLA) models have shown remarkable potential in visuomotor control and instruction comprehension through end-to-end learning processes. However, current VLA…
MMRo: Are Multimodal LLMs Eligible as the Brain for In-Home Robotics?
Jinming Li, Yichen Zhu, Zhiyuan Xu +7
It is fundamentally challenging for robots to serve as useful assistants in human environments because this requires addressing a spectrum of sub-problems across robotics, includin…
Mipha: A Comprehensive Overhaul of Multimodal Assistant with Small Language Models
Minjie Zhu, Yichen Zhu, Xin Liu +7
Multimodal Large Language Models (MLLMs) have showcased impressive skills in tasks related to visual understanding and reasoning. Yet, their widespread application faces obstacles…
Language-Conditioned Robotic Manipulation with Fast and Slow Thinking
Minjie Zhu, Yichen Zhu, Jinming Li +8
The language-conditioned robotic manipulation aims to transfer natural language instructions into executable actions, from simple pick-and-place to tasks requiring intent recogniti…
Object-Centric Instruction Augmentation for Robotic Manipulation
Junjie Wen, Yichen Zhu, Minjie Zhu +8
Humans interpret scenes by recognizing both the identities and positions of objects in their observations. For a robot to perform tasks such as \enquote{pick and place}, understand…
Visual Robotic Manipulation with Depth-Aware Pretraining
Wanying Wang, Jinming Li, Yichen Zhu +7
Recent work on visual representation learning has shown to be efficient for robotic manipulation tasks. However, most existing works pretrained the visual backbone solely on 2D ima…