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20242026
most citedQuantum-machine-assisted Drug Discovery

9 citations · 10 across the 24 of their papers we have counts for

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17 papers · 1 filter

cs.CV2026

Decoding Children's Gait Behavior

Yifan Shen, Boyi Li, Meihuan Huang +12

We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We specifically target the ambulator…

cs.CV2026

Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning

Jiahe Chen, Qian Shao, Qiyuan Chen +4

Open-set semi-supervised learning aims to leverage unlabeled data that may contain out-of-distribution outliers while maintaining performance on in-distribution classes. Existing m…

cs.CV2026

Med-Scout: Curing MLLMs' Geometric Blindness in Medical Perception via Geometry-Aware RL Post-Training

Anglin Liu, Ruichao Chen, Yi Lu +2

Despite recent Multimodal Large Language Models (MLLMs)' linguistic prowess in medical diagnosis, we find even state-of-the-art MLLMs suffer from a critical perceptual deficit: geo…

cs.CV2026

PHASE: Physiology-Aware Hyperspectral Reconstruction via Object-to-Human Domain Adaptation

Yufei Wen, Shuxing Zhong, Jingdan Kang +3

Although hyperspectral imaging offers unparalleled non-invasive physiological insight, its bulky hardware, slow acquisition, and regulatory burden severely limit its clinical avail…

cs.CV2026

Curing Semantic Drift: A Dynamic Approach to Grounding Generation in Large Vision-Language Models

Jiahe Chen, Jiaying He, Qiyuan Chen +6

Large Vision-Language Models (LVLMs) face a tug-of-war between powerful linguistic priors and visual evidence, often leading to \emph{semantic drift}: a progressive detachment from…

cs.CV20251 cited

MedSAM3: Delving into Segment Anything with Medical Concepts

Anglin Liu, Rundong Xue, Xu R. Cao +5

Medical image segmentation is fundamental for biomedical discovery. Existing methods lack generalizability and demand extensive, time-consuming manual annotation for new clinical a…