18 citations · 35 across the 8 of their papers we have counts for
10 papers
FastHarness: Experience-Driven Review Scheduling for Vision-Language-Action Policies
Tao Lin, Yuxin Du, Haoxiao Wang +2
Agentic robot systems combine language-model reasoning with robot policies to monitor execution and recover from failures. However, reviewing every action chunk incurs substantial…
Evo-DexBench: Benchmarking Generalization across Related Tasks for Dexterous Manipulation
Bing Cheng, Yiran Mao, Zewei Ye +10
General-purpose dexterous manipulation requires policies to transfer knowledge from related tasks to new tasks with only a few target demonstrations. Existing benchmarks often prov…
LA4VLA: Learning to Act without Seeing via Language-Action Pretraining
Tao Lin, Yuxin Du, Yiran Mao +13
Vision-Language-Action (VLA) models are commonly pretrained on robot demonstrations by jointly mapping visual observations and language instructions to actions. However, dense visu…
Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model
Tao Lin, Yuxin Du, Jiting Liu +14
Vision-Language-Action models have emerged as a promising paradigm for robotic manipulation by unifying perception, language grounding, and action generation. However, they often s…
Focusable Monocular Depth Estimation
Yuxin Du, Tao Lin, Zile Zhong +7
Monocular depth foundation models generalize well across scenes, yet they are typically optimized with uniform pixel-wise objectives that do not distinguish user-specified or task-…
Evo-1: Lightweight Vision-Language-Action Model with Preserved Semantic Alignment
Tao Lin, Yilei Zhong, Yuxin Du +11
Vision-Language-Action (VLA) models have emerged as a powerful framework that unifies perception, language, and control, enabling robots to perform diverse tasks through multimodal…
Multi-modal and Metadata Capture Model for Micro Video Popularity Prediction
Jiacheng Lu, Mingyuan Xiao, Weijian Wang +3
As short videos have become the primary form of content consumption across various industries, accurately predicting their popularity has become key to enhancing user engagement an…
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…
M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models
Fan Bai, Yuxin Du, Tiejun Huang +2
Medical image analysis is essential to clinical diagnosis and treatment, which is increasingly supported by multi-modal large language models (MLLMs). However, previous research ha…
SegVol: Universal and Interactive Volumetric Medical Image Segmentation
Yuxin Du, Fan Bai, Tiejun Huang +1
Precise image segmentation provides clinical study with instructive information. Despite the remarkable progress achieved in medical image segmentation, there is still an absence o…