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To address challenges in the digital economy's landscape of digital intelligence, large language models (LLMs) have been developed. Improvements in computational power and available resources have significantly advanced LLMs, allowing their…

Computation and Language · Computer Science 2024-05-24 Yanxin Zheng , Wensheng Gan , Zefeng Chen , Zhenlian Qi , Qian Liang , Philip S. Yu

Multilingual Large Language Models are capable of using powerful Large Language Models to handle and respond to queries in multiple languages, which achieves remarkable success in multilingual natural language processing tasks. Despite…

Computation and Language · Computer Science 2024-04-09 Libo Qin , Qiguang Chen , Yuhang Zhou , Zhi Chen , Yinghui Li , Lizi Liao , Min Li , Wanxiang Che , Philip S. Yu

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,…

Computation and Language · Computer Science 2024-12-04 Yunkai Dang , Kaichen Huang , Jiahao Huo , Yibo Yan , Sirui Huang , Dongrui Liu , Mengxi Gao , Jie Zhang , Chen Qian , Kun Wang , Yong Liu , Jing Shao , Hui Xiong , Xuming Hu

The recent emergence of Multi-modal Large Language Models (MLLMs) has introduced a new dimension to the Text-rich Image Understanding (TIU) field, with models demonstrating impressive and inspiring performance. However, their rapid…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Pei Fu , Tongkun Guan , Zining Wang , Zhentao Guo , Chen Duan , Hao Sun , Boming Chen , Jiayao Ma , Qianyi Jiang , Kai Zhou , Junfeng Luo

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

Large language models (LLMs) have demonstrated remarkable potential in handling multilingual machine translation (MMT). In this paper, we systematically investigate the advantages and challenges of LLMs for MMT by answering two questions:…

Computation and Language · Computer Science 2024-06-17 Wenhao Zhu , Hongyi Liu , Qingxiu Dong , Jingjing Xu , Shujian Huang , Lingpeng Kong , Jiajun Chen , Lei Li

In the rapidly evolving landscape of artificial intelligence (AI), generative large language models (LLMs) stand at the forefront, revolutionizing how we interact with our data. However, the computational intensity and memory consumption of…

Machine Learning · Computer Science 2025-07-24 Xupeng Miao , Gabriele Oliaro , Zhihao Zhang , Xinhao Cheng , Hongyi Jin , Tianqi Chen , Zhihao Jia

While large language models (LLMs) are still being adopted to new domains and utilized in novel applications, we are experiencing an influx of the new generation of foundation models, namely multi-modal large language models (MLLMs). These…

Computation and Language · Computer Science 2024-08-23 Kian Ahrabian , Zhivar Sourati , Kexuan Sun , Jiarui Zhang , Yifan Jiang , Fred Morstatter , Jay Pujara

Large Language Models (LLMs) have demonstrated their transformative potential across numerous disciplinary studies, reshaping the existing research methodologies and fostering interdisciplinary collaboration. However, a systematic…

Computation and Language · Computer Science 2025-07-14 Lu Xiang , Yang Zhao , Yaping Zhang , Chengqing Zong

Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as autonomous agents to do many tasks automatically. Recently,…

Computation and Language · Computer Science 2024-04-22 Taicheng Guo , Xiuying Chen , Yaqi Wang , Ruidi Chang , Shichao Pei , Nitesh V. Chawla , Olaf Wiest , Xiangliang Zhang

Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment. However, the…

Recent advances in large language models (LLMs) have unlocked novel opportunities for machine learning applications in the financial domain. These models have demonstrated remarkable capabilities in understanding context, processing vast…

General Finance · Quantitative Finance 2024-06-19 Yuqi Nie , Yaxuan Kong , Xiaowen Dong , John M. Mulvey , H. Vincent Poor , Qingsong Wen , Stefan Zohren

The advancement of Multimodal Large Language Models (MLLMs) has greatly accelerated the development of applications in understanding integrated texts and images. Recent works leverage image-caption datasets to train MLLMs, achieving…

Computation and Language · Computer Science 2024-11-22 Mingxu Tao , Quzhe Huang , Kun Xu , Liwei Chen , Yansong Feng , Dongyan Zhao

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

The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI's ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in…

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

Human-Computer Interaction · Computer Science 2024-04-10 M. Namvarpour , A. Razi

Large language models (LLMs) have revolutionized natural language processing by achieving state-of-the-art performance across various tasks. Recently, their effectiveness as embedding models has gained attention, marking a paradigm shift…

Computation and Language · Computer Science 2025-07-28 Chongyang Tao , Tao Shen , Shen Gao , Junshuo Zhang , Zhen Li , Kai Hua , Wenpeng Hu , Zhengwei Tao , Shuai Ma

Machine learning can provide deep insights into data, allowing machines to make high-quality predictions and having been widely used in real-world applications, such as text mining, visual classification, and recommender systems. However,…

Machine Learning · Computer Science 2020-08-11 Meng Wang , Weijie Fu , Xiangnan He , Shijie Hao , Xindong Wu

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by…

Computation and Language · Computer Science 2023-10-31 Yizhe Yang , Huashan Sun , Jiawei Li , Runheng Liu , Yinghao Li , Yuhang Liu , Heyan Huang , Yang Gao

Large Language Models (LLMs) have become extremely potent instruments with exceptional capacities for comprehending and producing human-like text in a wide range of applications. However, the increasing size and complexity of LLMs present…

Machine Learning · Computer Science 2024-06-18 Yingbing Huang , Lily Jiaxin Wan , Hanchen Ye , Manvi Jha , Jinghua Wang , Yuhong Li , Xiaofan Zhang , Deming Chen