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Related papers: A Comprehensive Review of Multimodal Large Languag…

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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

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

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

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

Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs), built upon LLMs, have demonstrated impressive potential in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Tao Yu , Yi-Fan Zhang , Chaoyou Fu , Junkang Wu , Jinda Lu , Kun Wang , Xingyu Lu , Yunhang Shen , Guibin Zhang , Dingjie Song , Yibo Yan , Tianlong Xu , Qingsong Wen , Zhang Zhang , Yan Huang , Liang Wang , Tieniu Tan

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…

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

In recent years, large language models have had a very impressive performance, which largely contributed to the development and application of artificial intelligence, and the parameters and performance of the models are still growing…

Machine Learning · Computer Science 2025-01-10 Xuran Zheng , Chang D. Yoo

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

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

Multimodal Large Language Models (MLLMs) mimic human perception and reasoning system by integrating powerful Large Language Models (LLMs) with various modality encoders (e.g., vision, audio), positioning LLMs as the "brain" and various…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Jiaxing Huang , Jingyi Zhang

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

Computation and Language · Computer Science 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

Multimodal Large Language Models (MLLMs) combine the natural language understanding and generation capabilities of LLMs with perception skills in modalities such as image and audio, representing a key advancement in contemporary AI. This…

In the past year, Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in tasks such as visual question answering, visual understanding and reasoning. However, the extensive model size and high training and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Yizhang Jin , Jian Li , Yexin Liu , Tianjun Gu , Kai Wu , Zhengkai Jiang , Muyang He , Bo Zhao , Xin Tan , Zhenye Gan , Yabiao Wang , Chengjie Wang , Lizhuang Ma

With the emergence of Large Language Models (LLMs) and Vision Foundation Models (VFMs), multimodal AI systems benefiting from large models have the potential to equally perceive the real world, make decisions, and control tools as humans.…

Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of research contributions in this direction. These works…

Computation and Language · Computer Science 2024-10-18 Humza Naveed , Asad Ullah Khan , Shi Qiu , Muhammad Saqib , Saeed Anwar , Muhammad Usman , Naveed Akhtar , Nick Barnes , Ajmal Mian

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…

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
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