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The comprehension of text-rich visual scenes has become a focal point for evaluating Multi-modal Large Language Models (MLLMs) due to their widespread applications. Current benchmarks tailored to the scenario emphasize perceptual…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Bin Shan , Xiang Fei , Wei Shi , An-Lan Wang , Guozhi Tang , Lei Liao , Jingqun Tang , Xiang Bai , Can Huang

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…

Computer Vision and Pattern Recognition · Computer Science 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

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…

Multimodal LLMs (MLLMs) are capable of performing complex data analysis, visual question answering, generation, and reasoning tasks. However, their ability to analyze biometric data is relatively underexplored. In this work, we investigate…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Ekta Gavas , Sudipta Banerjee , Chinmay Hegde , Nasir Memon

While Multimodal Large Language Models (MLLMs) have exhibited remarkable general intelligence across diverse domains, their potential in low-altitude applications dominated by Unmanned Aerial Vehicles (UAVs) remains largely underexplored.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Shiqi Dai , Zizhi Ma , Zhicong Luo , Xuesong Yang , Yibin Huang , Wanyue Zhang , Chi Chen , Zonghao Guo , Wang Xu , Yufei Sun , Maosong Sun

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

Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cultural contexts, respect local sensitivities, and support…

The rapid evolution of large language models (LLMs) holds promise for reforming the methodology of spatio-temporal data mining. However, current works for evaluating the spatio-temporal understanding capability of LLMs are somewhat limited…

Computation and Language · Computer Science 2024-06-28 Wenbin Li , Di Yao , Ruibo Zhao , Wenjie Chen , Zijie Xu , Chengxue Luo , Chang Gong , Quanliang Jing , Haining Tan , Jingping Bi

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to general-purpose reasoning. While current benchmarks have…

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

Large Language Models (LLMs) hold significant potential for advancing fact-checking by leveraging their capabilities in reasoning, evidence retrieval, and explanation generation. However, existing benchmarks fail to comprehensively evaluate…

Computation and Language · Computer Science 2025-06-17 Shuo Yang , Yuqin Dai , Guoqing Wang , Xinran Zheng , Jinfeng Xu , Jinze Li , Zhenzhe Ying , Weiqiang Wang , Edith C. H. Ngai

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…

Computer Vision and Pattern Recognition · Computer Science 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

Large language models (LLMs) have become increasingly pivotal across various domains, especially in handling complex data types. This includes structured data processing, as exemplified by ChartQA and ChatGPT-Ada, and multimodal…

Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only if they faithfully reflect real human behaviors. Current evaluations of simulation fidelity are…

Computation and Language · Computer Science 2026-04-14 Tiancheng Hu , Joachim Baumann , Lorenzo Lupo , Nigel Collier , Dirk Hovy , Paul Röttger

Multilingual Large Language Models (MLLMs) represent a pivotal advancement in democratizing artificial intelligence across linguistic boundaries. While theoretical foundations are well-established, practical implementation guidelines remain…

Computation and Language · Computer Science 2024-10-24 Junhua Liu , Bin Fu

Recent progress in Multimodal Large Language Models (MLLMs) has demonstrated remarkable advances in perception and reasoning, suggesting their potential for embodied intelligence. While recent studies have evaluated embodied MLLMs in…

Artificial Intelligence · Computer Science 2026-04-23 Shengyu Guo , Tongrui Ye , Jianbo Zhang , Zicheng Zhang , Chunyi Li , Guangtao Zhai

Sign language research has achieved significant progress due to the advances in large language models (LLMs). However, the intrinsic ability of LLMs to understand sign language, especially in multimodal contexts, remains underexplored. To…

Computation and Language · Computer Science 2026-04-27 Rui Zhao , Xuewen Zhong , Xiaoyun Zheng , Jinsong Su , Yidong Chen

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing to decision-making support systems. However, as these…

Computation and Language · Computer Science 2025-07-08 Jianchao Ji , Yutong Chen , Mingyu Jin , Wujiang Xu , Wenyue Hua , Yongfeng Zhang

There is widespread optimism that frontier Large Language Models (LLMs) and LLM-augmented systems have the potential to rapidly accelerate scientific discovery across disciplines. Today, many benchmarks exist to measure LLM knowledge and…

The popularity of multimodal large language models (MLLMs) has triggered a recent surge in research efforts dedicated to evaluating these models. Nevertheless, existing evaluation studies of MLLMs primarily focus on the comprehension and…

Computation and Language · Computer Science 2023-10-16 Xiaocui Yang , Wenfang Wu , Shi Feng , Ming Wang , Daling Wang , Yang Li , Qi Sun , Yifei Zhang , Xiaoming Fu , Soujanya Poria
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