1 citations · 1 across the 8 of their papers we have counts for
9 papers
Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Wanghan Xu, Yuhao Zhou, Yifan Zhou +104
Despite advances in scientific AI, a coherent framework for Scientific General Intelligence (SGI)-the ability to autonomously conceive, investigate, and reason across scientific do…
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…
UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis
Junzhi Ning, Wei Li, Cheng Tang +24
Medical workflows routinely combine reading images with producing visual and textual outputs, making both image understanding and generation central to medical AI. Most existing sy…
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…
EventRR: Event Referential Reasoning for Referring Video Object Segmentation
Huihui Xu, Jiashi Lin, Haoyu Chen +2
Referring Video Object Segmentation (RVOS) aims to segment out the object in a video referred by an expression. Current RVOS methods view referring expressions as unstructured sequ…
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…
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…
MedGround-R1: Advancing Medical Image Grounding via Spatial-Semantic Rewarded Group Relative Policy Optimization
Huihui Xu, Yuanpeng Nie, Hualiang Wang +9
Medical Image Grounding (MIG), which involves localizing specific regions in medical images based on textual descriptions, requires models to not only perceive regions but also ded…
RetinaLogos: Fine-Grained Synthesis of High-Resolution Retinal Images Through Captions
Junzhi Ning, Cheng Tang, Kaijing Zhou +12
The scarcity of high-quality, labelled retinal imaging data, which presents a significant challenge in the development of machine learning models for ophthalmology, hinders progres…