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Large multimodal models (LMMs) extend large language models (LLMs) with multi-sensory skills, such as visual understanding, to achieve stronger generic intelligence. In this paper, we analyze the latest model, GPT-4V(ision), to deepen the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Zhengyuan Yang , Linjie Li , Kevin Lin , Jianfeng Wang , Chung-Ching Lin , Zicheng Liu , Lijuan Wang

The development of large vision-language models (LVLMs) offers the potential to address challenges faced by traditional multimodal recommendations thanks to their proficient understanding of static images and textual dynamics. However, the…

Artificial Intelligence · Computer Science 2024-02-14 Yuqing Liu , Yu Wang , Lichao Sun , Philip S. Yu

Large language models (LLMs) have demonstrated a powerful ability to answer various queries as a general-purpose assistant. The continuous multi-modal large language models (MLLM) empower LLMs with the ability to perceive visual signals.…

Computation and Language · Computer Science 2024-01-05 Ziqiang Zheng , Yiwei Chen , Jipeng Zhang , Tuan-Anh Vu , Huimin Zeng , Yue Him Wong Tim , Sai-Kit Yeung

Recent research has offered insights into the extraordinary capabilities of Large Multimodal Models (LMMs) in various general vision and language tasks. There is growing interest in how LMMs perform in more specialized domains. Social media…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Hanjia Lyu , Jinfa Huang , Daoan Zhang , Yongsheng Yu , Xinyi Mou , Jinsheng Pan , Zhengyuan Yang , Zhongyu Wei , Jiebo Luo

Automatically evaluating vision-language tasks is challenging, especially when it comes to reflecting human judgments due to limitations in accounting for fine-grained details. Although GPT-4V has shown promising results in various…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Xinlu Zhang , Yujie Lu , Weizhi Wang , An Yan , Jun Yan , Lianke Qin , Heng Wang , Xifeng Yan , William Yang Wang , Linda Ruth Petzold

The emergence of multimodal large models (MLMs) has significantly advanced the field of visual understanding, offering remarkable capabilities in the realm of visual question answering (VQA). Yet, the true challenge lies in the domain of…

Computation and Language · Computer Science 2024-08-27 Yunxin Li , Longyue Wang , Baotian Hu , Xinyu Chen , Wanqi Zhong , Chenyang Lyu , Wei Wang , Min Zhang

In this paper, we critically evaluate the capabilities of the state-of-the-art multimodal large language model, i.e., GPT-4 with Vision (GPT-4V), on Visual Question Answering (VQA) task. Our experiments thoroughly assess GPT-4V's…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Zhiling Yan , Kai Zhang , Rong Zhou , Lifang He , Xiang Li , Lichao Sun

OpenAI's latest large vision-language model (LVLM), GPT-4V(ision), has piqued considerable interest for its potential in medical applications. Despite its promise, recent studies and internal reviews highlight its underperformance in…

Computation and Language · Computer Science 2023-12-13 Pengcheng Chen , Ziyan Huang , Zhongying Deng , Tianbin Li , Yanzhou Su , Haoyu Wang , Jin Ye , Yu Qiao , Junjun He

The surge of interest towards Multi-modal Large Language Models (MLLMs), e.g., GPT-4V(ision) from OpenAI, has marked a significant trend in both academia and industry. They endow Large Language Models (LLMs) with powerful capabilities in…

OpenAI's large multimodal model, GPT-4V(ision), was recently developed for general image interpretation. However, less is known about its capabilities with medical image interpretation and diagnosis. Board-certified physicians and senior…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Senthujan Senkaiahliyan , Augustin Toma , Jun Ma , An-Wen Chan , Andrew Ha , Kevin R. An , Hrishikesh Suresh , Barry Rubin , Bo Wang

Recent advancements in multimodal techniques open exciting possibilities for models excelling in diverse tasks involving text, audio, and image processing. Models like GPT-4V, blending computer vision and language modeling, excel in complex…

Computation and Language · Computer Science 2023-10-20 Xiang Zhang , Senyu Li , Zijun Wu , Ning Shi

The emergence of Large Multimodal Models (LMMs) marks a significant milestone in the development of artificial intelligence. Insurance, as a vast and complex discipline, involves a wide variety of data forms in its operational processes,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Chenwei Lin , Hanjia Lyu , Jiebo Luo , Xian Xu

The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabilities of GPT-4V in the realms of geography, environmental…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Chenjiao Tan , Qian Cao , Yiwei Li , Jielu Zhang , Xiao Yang , Huaqin Zhao , Zihao Wu , Zhengliang Liu , Hao Yang , Nemin Wu , Tao Tang , Xinyue Ye , Lilong Chai , Ninghao Liu , Changying Li , Lan Mu , Tianming Liu , Gengchen Mai

Driven by the large foundation models, the development of artificial intelligence has witnessed tremendous progress lately, leading to a surge of general interest from the public. In this study, we aim to assess the performance of OpenAI's…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Chaoyi Wu , Jiayu Lei , Qiaoyu Zheng , Weike Zhao , Weixiong Lin , Xiaoman Zhang , Xiao Zhou , Ziheng Zhao , Ya Zhang , Yanfeng Wang , Weidi Xie

This paper presents a comprehensive evaluation of the Optical Character Recognition (OCR) capabilities of the recently released GPT-4V(ision), a Large Multimodal Model (LMM). We assess the model's performance across a range of OCR tasks,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Yongxin Shi , Dezhi Peng , Wenhui Liao , Zening Lin , Xinhong Chen , Chongyu Liu , Yuyi Zhang , Lianwen Jin

The rapidly evolving sector of Multi-modal Large Language Models (MLLMs) is at the forefront of integrating linguistic and visual processing in artificial intelligence. This paper presents an in-depth comparative study of two pioneering…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Zhangyang Qi , Ye Fang , Mengchen Zhang , Zeyi Sun , Tong Wu , Ziwei Liu , Dahua Lin , Jiaqi Wang , Hengshuang Zhao

Recently, Multimodal Large Language Model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform multimodal tasks. The surprising emergent capabilities of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Shukang Yin , Chaoyou Fu , Sirui Zhao , Ke Li , Xing Sun , Tong Xu , Enhong Chen

Multimodal large language models (MLLMs) have shown remarkable capabilities across a broad range of tasks but their knowledge and abilities in the geographic and geospatial domains are yet to be explored, despite potential wide-ranging…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Jonathan Roberts , Timo Lüddecke , Rehan Sheikh , Kai Han , Samuel Albanie

The pursuit of autonomous driving technology hinges on the sophisticated integration of perception, decision-making, and control systems. Traditional approaches, both data-driven and rule-based, have been hindered by their inability to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Licheng Wen , Xuemeng Yang , Daocheng Fu , Xiaofeng Wang , Pinlong Cai , Xin Li , Tao Ma , Yingxuan Li , Linran Xu , Dengke Shang , Zheng Zhu , Shaoyan Sun , Yeqi Bai , Xinyu Cai , Min Dou , Shuanglu Hu , Botian Shi , Yu Qiao

As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and…

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