1 citations · 3 across the 18 of their papers we have counts for
9 papers · 1 filter
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…
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…
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…
Unified Medical Image Tokenizer for Autoregressive Synthesis and Understanding
Chenglong Ma, Yuanfeng Ji, Jin Ye +9
Autoregressive modeling has driven major advances in multimodal AI, yet its application to medical imaging remains constrained by the absence of a unified image tokenizer that simu…
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…
Towards Interpretable Counterfactual Generation via Multimodal Autoregression
Chenglong Ma, Yuanfeng Ji, Jin Ye +6
Counterfactual medical image generation enables clinicians to explore clinical hypotheses, such as predicting disease progression, facilitating their decision-making. While existin…