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Related papers: LLMs Meet Multimodal Generation and Editing: A Sur…

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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

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 paper offers an insightful examination of how currently top-trending AI technologies, i.e., generative artificial intelligence (Generative AI) and large language models (LLMs), are reshaping the field of video technology, including…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Pengyuan Zhou , Lin Wang , Zhi Liu , Yanbin Hao , Pan Hui , Sasu Tarkoma , Jussi Kangasharju

As Large Language Models (LLMs) and other forms of Generative AI permeate various aspects of our lives, their application for learning and education has provided opportunities and challenges. This paper presents an investigation into the…

Computers and Society · Computer Science 2023-06-06 Daniel Leiker , Sara Finnigan , Ashley Ricker Gyllen , Mutlu Cukurova

As Large Language Models (LLMs) become popular, there emerged an important trend of using multimodality to augment the LLMs' generation ability, which enables LLMs to better interact with the world. However, there lacks a unified perception…

Computation and Language · Computer Science 2023-12-04 Ruochen Zhao , Hailin Chen , Weishi Wang , Fangkai Jiao , Xuan Long Do , Chengwei Qin , Bosheng Ding , Xiaobao Guo , Minzhi Li , Xingxuan Li , Shafiq Joty

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

Multi-modal generative AI (Artificial Intelligence) has attracted increasing attention from both academia and industry. Particularly, two dominant families of techniques have emerged: i) Multi-modal large language models (LLMs) demonstrate…

Artificial Intelligence · Computer Science 2025-11-26 Xin Wang , Yuwei Zhou , Bin Huang , Hong Chen , Wenwu Zhu

The emergence of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has marked a new era of Natural Language Processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This paper…

Computation and Language · Computer Science 2024-08-26 Desta Haileselassie Hagos , Rick Battle , Danda B. Rawat

The rapid advancement of large language models (LLMs) and multimodal learning has transformed digital content creation and manipulation. Traditional visual editing tools require significant expertise, limiting accessibility. Recent strides…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Thanh Tam Nguyen , Zhao Ren , Trinh Pham , Thanh Trung Huynh , Phi Le Nguyen , Hongzhi Yin , Quoc Viet Hung Nguyen

Multimodal Large Models (MLMs) are becoming a significant research focus, combining powerful large language models with multimodal learning to perform complex tasks across different data modalities. This review explores the latest…

Machine Learning · Computer Science 2024-07-02 Xinji Mai , Zeng Tao , Junxiong Lin , Haoran Wang , Yang Chang , Yanlan Kang , Yan Wang , Wenqiang Zhang

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 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

The integration of Artificial Intelligence (AI), particularly Large Language Model (LLM)-based systems, in education has shown promise in enhancing teaching and learning experiences. However, the advent of Multimodal Large Language Models…

Large language models (LLMs) have achieved superior performance in powering text-based AI agents, endowing them with decision-making and reasoning abilities akin to humans. Concurrently, there is an emerging research trend focused on…

Computer Vision and Pattern Recognition · Computer Science 2024-02-26 Junlin Xie , Zhihong Chen , Ruifei Zhang , Xiang Wan , Guanbin Li

This paper presents an in-depth survey on the use of multimodal Generative Artificial Intelligence (GenAI) and autoregressive Large Language Models (LLMs) for human motion understanding and generation, offering insights into emerging…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Muhammad Islam , Tao Huang , Euijoon Ahn , Usman Naseem

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 rapid progress of Multimodal Large Language Models(MLLMs) has transformed the AI landscape. These models combine pre-trained LLMs with various modality encoders. This integration requires a systematic understanding of how different…

Computation and Language · Computer Science 2025-06-06 Jisu An , Junseok Lee , Jeoungeun Lee , Yongseok Son

In recent years, large language models (LLMs) have driven major advances in language understanding, marking a significant step toward artificial general intelligence (AGI). With increasing demands for higher-level semantics and cross-modal…

Computation and Language · Computer Science 2025-09-30 Yuntao Shou , Tao Meng , Wei Ai , Keqin Li

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

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
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