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Multimodal Large Language Models (MLLMs) have exhibited immense potential across numerous medical specialties; yet, dentistry remains underexplored, in part due to limited domain-specific data, scarce dental expert annotations, insufficient…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jing Hao , Yuci Liang , Lizhuo Lin , Yuxuan Fan , Wenkai Zhou , Kaixin Guo , Zanting Ye , Yanpeng Sun , Xinyu Zhang , Yanqi Yang , Qiankun Li , Hao Tang , James Kit-Hon Tsoi , Linlin Shen , Kuo Feng Hung

Recent advances in large vision-language models (LVLMs) have demonstrated strong performance on general-purpose medical tasks. However, their effectiveness in specialized domains such as dentistry remains underexplored. In particular,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Jing Hao , Yuxuan Fan , Yanpeng Sun , Kaixin Guo , Lizhuo Lin , Jinrong Yang , Qi Yong H. Ai , Lun M. Wong , Hao Tang , Kuo Feng Hung

Multimodal large language models (MLLMs) have emerged as a promising paradigm for dental image analysis. However, their ability to capture the multi-level cognitive processes required for radiographic analysis remains unclear. Here, we…

Computation and Language · Computer Science 2026-05-11 Rongyang Wang , Shuang Zhou , Jiashuo Wang , Wenya Xie , Xiaoxia Che

Recently, Multimodal Large Language Models (MLLMs) have gained significant attention for their remarkable ability to process and analyze non-textual data, such as images, videos, and audio. Notably, several adaptations of general-domain…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Wenhui Zhu , Xin Li , Xiwen Chen , Peijie Qiu , Vamsi Krishna Vasa , Xuanzhao Dong , Yanxi Chen , Natasha Lepore , Oana Dumitrascu , Yi Su , Yalin Wang

Multimodal Large Language Models (MLLMs) show promise for medical applications, yet progress in dermatology lags due to limited training data, narrow task coverage, and lack of clinically-grounded supervision that mirrors expert diagnostic…

Computation and Language · Computer Science 2026-01-06 Jinghan Ru , Siyuan Yan , Yuguo Yin , Yuexian Zou , Zongyuan Ge

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among…

Computation and Language · Computer Science 2023-08-01 Hanyao Huang , Ou Zheng , Dongdong Wang , Jiayi Yin , Zijin Wang , Shengxuan Ding , Heng Yin , Chuan Xu , Renjie Yang , Qian Zheng , Bing Shi

Multimodal Large Language Models (MLLMs) are widely regarded as crucial in the exploration of Artificial General Intelligence (AGI). The core of MLLMs lies in their capability to achieve cross-modal alignment. To attain this goal, current…

Computation and Language · Computer Science 2024-11-26 Fei Zhao , Taotian Pang , Chunhui Li , Zhen Wu , Junjie Guo , Shangyu Xing , Xinyu Dai

Oral mucosal diseases such as leukoplakia, oral lichen planus, and recurrent aphthous ulcers exhibit diverse and overlapping visual features, making diagnosis challenging for non-specialists. While vision-language models (VLMs) have shown…

Quantitative Methods · Quantitative Biology 2025-10-17 Jia Zhang , Bodong Du , Yitong Miao , Dongwei Sun , Xiangyong Cao

Diagnosing and managing oral diseases necessitate advanced visual interpretation across diverse imaging modalities and integrated information synthesis. While current AI models excel at isolated tasks, they often fall short in addressing…

Multimodal large language models (MLLMs) have emerged as a prominent area of interest within the research community, given their proficiency in handling and reasoning with non-textual data, including images and videos. This study seeks to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Zhenhua Xu , Yujia Zhang , Enze Xie , Zhen Zhao , Yong Guo , Kwan-Yee. K. Wong , Zhenguo Li , Hengshuang Zhao

In the past five years, research has shifted from traditional Machine Learning (ML) and Deep Learning (DL) approaches to leveraging Large Language Models (LLMs) , including multimodality, for data augmentation to enhance generalization, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Ranjan Sapkota , Shaina Raza , Maged Shoman , Achyut Paudel , Manoj Karkee

Digital dentistry has made significant advances with the advent of deep learning. However, the majority of these deep learning-based dental image analysis models focus on very specific tasks such as tooth segmentation, tooth detection,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Anastasiia Sukhanova , Aiden Taylor , Julian Myers , Zichun Wang , Kartha Veerya Jammuladinne , Satya Sri Rajiteswari Nimmagadda , Aniruddha Maiti , Ananya Jana

Large language models have exhibited exceptional performance on various Natural Language Processing (NLP) tasks, leveraging techniques such as the pre-training, and instruction fine-tuning. Despite these advances, their effectiveness in…

Computation and Language · Computer Science 2023-06-19 Guangyu Wang , Guoxing Yang , Zongxin Du , Longjun Fan , Xiaohu Li

Vision-Language Models (VLMs) have demonstrated significant potential in medical image analysis, yet their application in intraoral photography remains largely underexplored due to the lack of fine-grained, annotated datasets and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Meng-Xun Li , Wen-Hui Deng , Zhi-Xing Wu , Chun-Xiao Jin , Jia-Min Wu , Yue Han , James Kit Hon Tsoi , Gui-Song Xia , Cui Huang

Multimodal large language models (MLLMs) have shown remarkable performance in vision-language tasks. However, existing MLLMs are primarily trained on generic datasets, limiting their ability to reason on domain-specific visual cues such as…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Hatef Otroshi Shahreza , Sébastien Marcel

Multimodal large language models (MLLMs) have achieved impressive performance across various tasks such as image captioning and visual question answer(VQA); however, they often struggle to accurately interpret depth information inherent in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Hao Yang , Hongbo Zhang , Yanyan Zhao , Bing Qin

While large language models (LLMs) hold transformative potential for medicine, their reasoning robustness and safety in real-world clinical scenarios remain critically underexplored, particularly in dentistry. Here we introduce…

Multi-modal large language models (MLLMs) have demonstrated remarkable success in vision and visual-language tasks within the natural image domain. Owing to the significant diversities between the natural and remote sensing (RS) images, the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-11 Wei Zhang , Miaoxin Cai , Tong Zhang , Yin Zhuang , Xuerui Mao

Large Language Models (LLMs) possess human-level cognitive and decision-making capabilities, making them a key technology for 6G. However, applying LLMs to the communication domain faces three major challenges: 1) Inadequate communication…

Information Theory · Computer Science 2025-02-27 Feibo Jiang , Wanyun Zhu , Li Dong , Kezhi Wang , Kun Yang , Cunhua Pan , Octavia A. Dobre

Recent advances in large language models (LLMs) and medical LLMs (Med-LLMs) have demonstrated strong performance on general medical benchmarks. However, their capabilities in specialized medical fields, such as dentistry which require…

Computation and Language · Computer Science 2025-08-29 Hengchuan Zhu , Yihuan Xu , Yichen Li , Zijie Meng , Zuozhu Liu
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