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Large Language Models (LLMs) have rapidly evolved from text-based systems to multimodal platforms, significantly impacting various sectors including healthcare. This comprehensive review explores the progression of LLMs to Multimodal Large…

Connecting text and visual modalities plays an essential role in generative intelligence. For this reason, inspired by the success of large language models, significant research efforts are being devoted to the development of Multimodal…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Davide Caffagni , Federico Cocchi , Luca Barsellotti , Nicholas Moratelli , Sara Sarto , Lorenzo Baraldi , Lorenzo Baraldi , Marcella Cornia , Rita Cucchiara

This survey and application guide to multimodal large language models(MLLMs) explores the rapidly developing field of MLLMs, examining their architectures, applications, and impact on AI and Generative Models. Starting with foundational…

Artificial Intelligence · Computer Science 2025-12-02 Chia Xin Liang , Pu Tian , Caitlyn Heqi Yin , Yao Yua , Wei An-Hou , Li Ming , Xinyuan Song , Tianyang Wang , Ziqian Bi , Ming Liu

The exploration of multimodal language models integrates multiple data types, such as images, text, language, audio, and other heterogeneity. While the latest large language models excel in text-based tasks, they often struggle to…

Artificial Intelligence · Computer Science 2023-11-23 Jiayang Wu , Wensheng Gan , Zefeng Chen , Shicheng Wan , Philip S. Yu

The rise of Multimodal Large Language Models (MLLMs) has become a transformative force in the field of artificial intelligence, enabling machines to process and generate content across multiple modalities, such as text, images, audio, and…

Computation and Language · Computer Science 2025-12-09 Ming Li , Keyu Chen , Ziqian Bi , Ming Liu , Xinyuan Song , Zekun Jiang , Tianyang Wang , Benji Peng , Qian Niu , Junyu Liu , Jinlang Wang , Sen Zhang , Xuanhe Pan , Jiawei Xu , Pohsun Feng

Multimodal models are expected to be a critical component to future advances in artificial intelligence. This field is starting to grow rapidly with a surge of new design elements motivated by the success of foundation models in natural…

Computation and Language · Computer Science 2024-06-11 Sai Munikoti , Ian Stewart , Sameera Horawalavithana , Henry Kvinge , Tegan Emerson , Sandra E Thompson , Karl Pazdernik

The advent of Large Language Models (LLMs) has significantly reshaped the trajectory of the AI revolution. Nevertheless, these LLMs exhibit a notable limitation, as they are primarily adept at processing textual information. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-10-15 Akash Ghosh , Arkadeep Acharya , Sriparna Saha , Vinija Jain , Aman Chadha

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

Large Language Models (LLMs) have recently emerged as a focal point of research and application, driven by their unprecedented ability to understand and generate text with human-like quality. Even more recently, LLMs have been extended into…

Computation and Language · Computer Science 2024-04-03 Kilian Carolan , Laura Fennelly , Alan F. Smeaton

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

Machine Learning · Computer Science 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique

In an era defined by the explosive growth of data and rapid technological advancements, Multimodal Large Language Models (MLLMs) stand at the forefront of artificial intelligence (AI) systems. Designed to seamlessly integrate diverse data…

The rapid evolution of Multimodal Large Language Models (MLLMs) has brought substantial advancements in artificial intelligence, significantly enhancing the capability to understand and generate multimodal content. While prior studies have…

Artificial Intelligence · Computer Science 2024-09-30 Lin Li , Guikun Chen , Hanrong Shi , Jun Xiao , Long Chen

The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with large language models (LLMs) and computer vision (CV) systems driving advancements in natural language understanding and visual processing,…

Computation and Language · Computer Science 2024-12-04 Yunkai Dang , Kaichen Huang , Jiahao Huo , Yibo Yan , Sirui Huang , Dongrui Liu , Mengxi Gao , Jie Zhang , Chen Qian , Kun Wang , Yong Liu , Jing Shao , Hui Xiong , Xuming Hu

Multimodal large language models (MLLMs) enhance the capabilities of standard large language models by integrating and processing data from multiple modalities, including text, vision, audio, video, and 3D environments. Data plays a pivotal…

Artificial Intelligence · Computer Science 2024-07-19 Tianyi Bai , Hao Liang , Binwang Wan , Yanran Xu , Xi Li , Shiyu Li , Ling Yang , Bozhou Li , Yifan Wang , Bin Cui , Ping Huang , Jiulong Shan , Conghui He , Binhang Yuan , Wentao Zhang

As a prominent direction of Artificial General Intelligence (AGI), Multimodal Large Language Models (MLLMs) have garnered increased attention from both industry and academia. Building upon pre-trained LLMs, this family of models further…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Chaoyou Fu , Yi-Fan Zhang , Shukang Yin , Bo Li , Xinyu Fang , Sirui Zhao , Haodong Duan , Xing Sun , Ziwei Liu , Liang Wang , Caifeng Shan , Ran He

Multimodal learning, a rapidly evolving field in artificial intelligence, seeks to construct more versatile and robust systems by integrating and analyzing diverse types of data, including text, images, audio, and video. Inspired by the…

Artificial Intelligence · Computer Science 2024-12-24 Priyaranjan Pattnayak , Hitesh Laxmichand Patel , Bhargava Kumar , Amit Agarwal , Ishan Banerjee , Srikant Panda , Tejaswini Kumar

Recent advancements in Large Multimodal Models (LMMs) have attracted interest in their generalization capability with only a few samples in the prompt. This progress is particularly relevant to the medical domain, where the quality and…

Computation and Language · Computer Science 2024-05-06 Seonhee Cho , Choonghan Kim , Jiho Lee , Chetan Chilkunda , Sujin Choi , Joo Heung Yoon

Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as text, images, and audio, to perform complex tasks with high…

With the advent of Large Language Models (LLMs), medical artificial intelligence (AI) has experienced substantial technological progress and paradigm shifts, highlighting the potential of LLMs to streamline healthcare delivery and improve…

Computation and Language · Computer Science 2024-12-10 Lei Liu , Xiaoyan Yang , Junchi Lei , Yue Shen , Jian Wang , Peng Wei , Zhixuan Chu , Zhan Qin , Kui Ren

The recent emergence of Multi-modal Large Language Models (MLLMs) has introduced a new dimension to the Text-rich Image Understanding (TIU) field, with models demonstrating impressive and inspiring performance. However, their rapid…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Pei Fu , Tongkun Guan , Zining Wang , Zhentao Guo , Chen Duan , Hao Sun , Boming Chen , Jiayao Ma , Qianyi Jiang , Kai Zhou , Junfeng Luo
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