2 citations · 3 across the 9 of their papers we have counts for
9 papers
Gaze Target Estimation Anywhere with Concepts
Xu Cao, Houze Yang, Vipin Gunda +5
Estimating human gaze targets from images in-the-wild is an important and formidable task. Existing approaches primarily employ brittle, multi-stage pipelines that require explicit…
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…
dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model
Yaxuan Li, Zhongyi Zhou, Yefei Chen +2
Evaluating robotics policies across thousands of environments and thousands of tasks is infeasible with existing approaches. This motivates the need for a new methodology for scala…
ActiveUMI: Robotic Manipulation with Active Perception from Robot-Free Human Demonstrations
Qiyuan Zeng, Chengmeng Li, Jude St. John +5
We present ActiveUMI, a framework for a data collection system that transfers in-the-wild human demonstrations to robots capable of complex bimanual manipulation. ActiveUMI couples…
ChatVLA-2: Vision-Language-Action Model with Open-World Embodied Reasoning from Pretrained Knowledge
Zhongyi Zhou, Yichen Zhu, Junjie Wen +2
Vision-language-action (VLA) models have emerged as the next generation of models in robotics. However, despite leveraging powerful pre-trained Vision-Language Models (VLMs), exist…
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…
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…