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Multimodal Large Language Models (MLLMs) are gaining increasing popularity in both academia and industry due to their remarkable performance in various applications such as visual question answering, visual perception, understanding, and…

计算与语言 · 计算机科学 2024-09-09 Jian Li , Weiheng Lu , Hao Fei , Meng Luo , Ming Dai , Min Xia , Yizhang Jin , Zhenye Gan , Ding Qi , Chaoyou Fu , Ying Tai , Wankou Yang , Yabiao Wang , Chengjie Wang

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…

人工智能 · 计算机科学 2024-09-30 Lin Li , Guikun Chen , Hanrong Shi , Jun Xiao , Long Chen

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…

计算机视觉与模式识别 · 计算机科学 2024-08-29 Jiaxing Huang , Jingyi Zhang

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…

Strong Artificial Intelligence (Strong AI) or Artificial General Intelligence (AGI) with abstract reasoning ability is the goal of next-generation AI. Recent advancements in Large Language Models (LLMs), along with the emerging field of…

计算与语言 · 计算机科学 2024-01-19 Yiqi Wang , Wentao Chen , Xiaotian Han , Xudong Lin , Haiteng Zhao , Yongfei Liu , Bohan Zhai , Jianbo Yuan , Quanzeng You , Hongxia Yang

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…

计算与语言 · 计算机科学 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 Model (MLLM) relies on the powerful LLM to perform multimodal tasks, showing amazing emergent abilities in recent studies, such as writing poems based on an image. However, it is difficult for these case studies to…

计算机视觉与模式识别 · 计算机科学 2025-10-27 Chaoyou Fu , Peixian Chen , Yunhang Shen , Yulei Qin , Mengdan Zhang , Xu Lin , Jinrui Yang , Xiawu Zheng , Ke Li , Xing Sun , Yunsheng Wu , Rongrong Ji , Caifeng Shan , Ran He

Multimodal large language models (MLLMs) have broadened the scope of AI applications. Existing automatic evaluation methodologies for MLLMs are mainly limited in evaluating queries without considering user experiences, inadequately…

The rapid advancement of Multimodal Large Language Models (MLLMs) has been accompanied by the development of various benchmarks to evaluate their capabilities. However, the true nature of these evaluations and the extent to which they…

计算与语言 · 计算机科学 2024-10-17 Botian Jiang , Lei Li , Xiaonan Li , Zhaowei Li , Xiachong Feng , Lingpeng Kong , Qi Liu , Xipeng Qiu

Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence. These models not only excel in traditional vision-language tasks but also demonstrate impressive performance in contemporary…

计算机视觉与模式识别 · 计算机科学 2023-12-06 Xiaotian Han , Quanzeng You , Yongfei Liu , Wentao Chen , Huangjie Zheng , Khalil Mrini , Xudong Lin , Yiqi Wang , Bohan Zhai , Jianbo Yuan , Heng Wang , Hongxia Yang

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…

Mathematical reasoning, a core aspect of human cognition, is vital across many domains, from educational problem-solving to scientific advancements. As artificial general intelligence (AGI) progresses, integrating large language models…

计算与语言 · 计算机科学 2025-05-21 Yibo Yan , Jiamin Su , Jianxiang He , Fangteng Fu , Xu Zheng , Yuanhuiyi Lyu , Kun Wang , Shen Wang , Qingsong Wen , Xuming Hu

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…

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,…

Multimodal Large Language Models (MLLMs) have gained significant attention recently, showing remarkable potential in artificial general intelligence. However, assessing the utility of MLLMs presents considerable challenges, primarily due to…

计算与语言 · 计算机科学 2024-06-12 Dongping Chen , Ruoxi Chen , Shilin Zhang , Yinuo Liu , Yaochen Wang , Huichi Zhou , Qihui Zhang , Yao Wan , Pan Zhou , Lichao Sun

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…

计算与语言 · 计算机科学 2025-09-30 Yuntao Shou , Tao Meng , Wei Ai , Keqin Li

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…

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…

人工智能 · 计算机科学 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 Multimodal Large Language Model (MLLM) is currently experiencing rapid growth, driven by the advanced capabilities of LLMs. Unlike earlier specialists, existing MLLMs are evolving towards a Multimodal Generalist paradigm. Initially…

Multimodal large language models (MLLMs) have shown great potential in perception and interpretation tasks, but their capabilities in predictive reasoning remain under-explored. To address this gap, we introduce a novel benchmark that…

计算机视觉与模式识别 · 计算机科学 2023-10-23 Mingwei Zhu , Leigang Sha , Yu Shu , Kangjia Zhao , Tiancheng Zhao , Jianwei Yin
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