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Multimodal Large Language Models: A Survey [PDF]

2023 IEEE International Conference on Big Data (BigData), 2023
IEEE BigData 2023.
Philip Yu, Wensheng Gan, Zefeng Chen
exaly   +5 more sources

A survey on multimodal large language models [PDF]

National Science Review
ABSTRACT Recently, the 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 the MLLM, such as writing stories based on images and optical character recognition ...
Xing Sun, Enhong Chen
exaly   +6 more sources

Benchmarking multimodal large language models for medicinal plant identification [PDF]

Frontiers in Plant Science
With the rapid advancement of artificial intelligence technology, large language models (LLMs) have shown considerable potential in the medical field.
Yue Jiang, Zhenzhong Dai, Wen Jin, Weinan Lin, Yijun Xu, Jiangda Wang, Zhaoxi Fang, Zhaoxi Fang, Zhaoxi Fang   +8 more
doaj   +2 more sources

Efficient multimodal large language models: a survey

Visual Intelligence
In the past years, multimodal large language models (MLLMs) have demonstrated remarkable performance in tasks such as visual question answering and visual understanding and reasoning.
Yizhang Jin, Jian Li, Tianjun Gu, Yexin Liu, Bo Zhao, Jinxiang Lai, Zhenye Gan, Yabiao Wang, Chengjie Wang, Xin Tan, Lizhuang Ma   +10 more
doaj   +4 more sources

Large-scale evaluation of multimodal large language models for pneumothorax detection [PDF]

Diagnostic and Interventional Radiology
PURPOSE: Pneumothorax requires rapid recognition and accurate interpretation of chest X-rays (CXRs), particularly in acute settings where delays can have serious consequences.
Hamza Eren Güzel, Cemre Özenbaş, Ali Murat Koç   +2 more
doaj   +2 more sources

Multimodal large language models challenge NEJM image challenge [PDF]

Scientific Reports
Current evaluations of Large Language Models (LLMs) in medicine primarily focus on text-based benchmarks, leaving their multimodal diagnostic capabilities in complex, real-world clinical scenarios largely undefined. Furthermore, comparisons against large-
Chiyu Sheng, Shumin Shen, Lin Wang, Jie Chen, Wei Chen, Shanghu Wang, Nianfei Wang   +6 more
doaj   +2 more sources

From Large Language Models to Large Multimodal Models: A Literature Review

Applied Sciences
With the deepening of research on Large Language Models (LLMs), significant progress has been made in recent years on the development of Large Multimodal Models (LMMs), which are gradually moving toward Artificial General Intelligence. This paper aims to
Dawei Huang, Chuan Yan, Qing Li, Xiaojiang Peng   +3 more
doaj   +3 more sources

A comprehensive survey of large language models and multimodal large language models in medicine

Information Fusion
Since the release of ChatGPT and GPT-4, large language models (LLMs) and multimodal large language models (MLLMs) have attracted widespread attention for their exceptional capabilities in understanding, reasoning, and generation, introducing transformative paradigms for integrating artificial intelligence into medicine.
Hanguang Xiao, Tianqi Liu
exaly   +3 more sources

Applications of Large Language Models and Multimodal Large Models in Autonomous Driving: A Comprehensive Review

Drones
The rapid development of large language models (LLMs) and multimodal large models (MLMs) has introduced transformative opportunities for autonomous driving systems.
Jing Li, Jingyuan Li, Guo Yang, Lie Yang, Haozhuang Chi, Lichao Yang   +5 more
doaj   +3 more sources

Large language models and multimodal foundation models for precision oncology

npj Precision Oncology
The technological progress in artificial intelligence (AI) has massively accelerated since 2022, with far-reaching implications for oncology and cancer research.
Daniel Truhn, Jan-Niklas Eckardt, Dyke Ferber, Jakob Nikolas Kather   +3 more
doaj   +4 more sources