6 papers
SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models
Hongxiang Li, Hongxu Chen, Chenyang Zhu +5
Multimodal Large Language Models (MLLMs) have achieved remarkable success in visual understanding but remain constrained in visual generation due to the fundamental feature discrep…
Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine
Xiaoshuang Huang, Lingdong Shen, Jia Liu +4
In recent years, Multimodal Large Language Models (MLLM) have achieved notable advancements, demonstrating the feasibility of developing an intelligent biomedical assistant. Howeve…
A Refer-and-Ground Multimodal Large Language Model for Biomedicine
Xiaoshuang Huang, Haifeng Huang, Lingdong Shen +4
With the rapid development of multimodal large language models (MLLMs), especially their capabilities in visual chat through refer and ground functionalities, their significance is…
Textual Inversion and Self-supervised Refinement for Radiology Report Generation
Yuanjiang Luo, Hongxiang Li, Xuan Wu +6
Existing mainstream approaches follow the encoder-decoder paradigm for generating radiology reports. They focus on improving the network structure of encoders and decoders, which l…
Cross-Modal Conditioned Reconstruction for Language-guided Medical Image Segmentation
Xiaoshuang Huang, Hongxiang Li, Meng Cao +3
Recent developments underscore the potential of textual information in enhancing learning models for a deeper understanding of medical visual semantics. However, language-guided me…
SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging
Lingdong Shen, Fangxin Shang, Xiaoshuang Huang +3
In the field of medical image segmentation, tackling Out-of-Distribution (OOD) segmentation tasks in a cost-effective manner remains a significant challenge. Universal segmentation…