most citedSegBook: A Simple Baseline and Cookbook for Volumetric Medical Image Segmentation

1 citations · 2 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2025

MedQ-Bench: Evaluating and Exploring Medical Image Quality Assessment Abilities in MLLMs

Jiyao Liu, Jinjie Wei, Wanying Qu +17

Medical Image Quality Assessment (IQA) serves as the first-mile safety gate for clinical AI, yet existing approaches remain constrained by scalar, score-based metrics and fail to r…

cs.CL2025

SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines

Yizhou Wang, Chen Tang, Han Deng +29

We present a scientific reasoning foundation model that aligns natural language with heterogeneous scientific representations. The model is pretrained on a 206B-token corpus spanni…

cs.CV2025

S2-UniSeg: Fast Universal Agglomerative Pooling for Scalable Segment Anything without Supervision

Huihui Xu, Jin Ye, Hongqiu Wang +10

Recent self-supervised image segmentation models have achieved promising performance on semantic segmentation and class-agnostic instance segmentation. However, their pretraining s…

cs.CL20251 cited

A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers

Ming Hu, Chenglong Ma, Wei Li +117

Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the compl…

cs.IR2025

Enhancing Retrieval-Augmented Generation for Electric Power Industry Customer Support

Hei Yu Chan, Kuok Tou Ho, Chenglong Ma +3

Many AI customer service systems use standard NLP pipelines or finetuned language models, which often fall short on ambiguous, multi-intent, or detail-specific queries. This case s…

cs.CV2025

GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical Reasoning

Yanzhou Su, Tianbin Li, Jiyao Liu +15

Recent advances in general medical AI have made significant strides, but existing models often lack the reasoning capabilities needed for complex medical decision-making. This pape…