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Large language models (LLMs) are a class of language models that have demonstrated outstanding performance across a range of natural language processing (NLP) tasks and have become a highly sought-after research area, because of their…

Digital Libraries · Computer Science 2023-04-06 Lizhou Fan , Lingyao Li , Zihui Ma , Sanggyu Lee , Huizi Yu , Libby Hemphill

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large…

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

Large Language Models (LLMs) have fundamentally transformed approaches to Natural Language Processing (NLP) tasks across diverse domains. In healthcare, accurate and cost-efficient text classification is crucial, whether for clinical notes…

Computation and Language · Computer Science 2026-02-16 Hajar Sakai , Sarah S. Lam

Large Language Models (LLMs) trained on extensive textual corpora have emerged as leading solutions for a broad array of Natural Language Processing (NLP) tasks. Despite their notable performance, these models are prone to certain…

Computation and Language · Computer Science 2023-07-25 Yufei Wang , Wanjun Zhong , Liangyou Li , Fei Mi , Xingshan Zeng , Wenyong Huang , Lifeng Shang , Xin Jiang , Qun Liu

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

Tool learning has emerged as a promising direction by extending Large Language Models' (LLMs) capabilities with external tools. Existing tool learning studies primarily focus on the general-purpose tool-use capability, which addresses…

Computation and Language · Computer Science 2025-02-27 Qiancheng Xu , Yongqi Li , Heming Xia , Fan Liu , Min Yang , Wenjie Li

Large language models (LLMs) offer emerging opportunities for psychological and behavioral research, but methodological guidance is lacking. This article provides a framework for using LLMs as psychological simulators across two primary…

Computers and Society · Computer Science 2026-04-07 Zhicheng Lin

With the rapid development of artificial intelligence, large language models (LLMs) have shown promising capabilities in mimicking human-level language comprehension and reasoning. This has sparked significant interest in applying LLMs to…

Computation and Language · Computer Science 2023-11-06 Mingze Yuan , Peng Bao , Jiajia Yuan , Yunhao Shen , Zifan Chen , Yi Xie , Jie Zhao , Yang Chen , Li Zhang , Lin Shen , Bin Dong

Large language models (LLMs) have transformed many fields, including natural language processing, computer vision, and reinforcement learning. These models have also made a significant impact in the field of law, where they are being…

Computation and Language · Computer Science 2023-03-17 Zhongxiang Sun

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

Machine Learning · Computer Science 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique

Large language models (LLMs) have become the secret ingredient driving numerous industrial applications, showcasing their remarkable versatility across a diverse spectrum of tasks. From natural language processing and sentiment analysis to…

Large Language Models (LLMs) have shown capabilities close to human performance in various analytical tasks, leading researchers to use them for time and labor-intensive analyses. However, their capability to handle highly specialized and…

Computation and Language · Computer Science 2024-10-08 Alexander S. Choi , Syeda Sabrina Akter , JP Singh , Antonios Anastasopoulos

Large Language Models (LLMs) are increasingly employed for simulating human behaviors across diverse domains. However, our position is that current LLM-based human simulations remain insufficiently reliable, as evidenced by significant…

Computation and Language · Computer Science 2025-12-02 Qian Wang , Jiaying Wu , Zichen Jiang , Zhenheng Tang , Bingqiao Luo , Nuo Chen , Wei Chen , Bingsheng He

Large Language Models (LLMs) have demonstrated surprising performance across various natural language processing tasks. Recently, medical LLMs enhanced with domain-specific knowledge have exhibited excellent capabilities in medical…

Computation and Language · Computer Science 2024-09-24 Jinqiang Wang , Huansheng Ning , Yi Peng , Qikai Wei , Daniel Tesfai , Wenwei Mao , Tao Zhu , Runhe Huang

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify the remaining challenges and already fruitful application…

Computation and Language · Computer Science 2023-07-20 Jean Kaddour , Joshua Harris , Maximilian Mozes , Herbie Bradley , Roberta Raileanu , Robert McHardy

The development and evaluation of Large Language Models (LLMs) has primarily focused on their task-solving capabilities, with recent models even surpassing human performance in some areas. However, this focus often neglects whether…

Computation and Language · Computer Science 2025-07-29 Yanzhu Guo , Guokan Shang , Chloé Clavel

Large Language Models (LLMs) are rapidly reshaping machine translation (MT), particularly by introducing instruction-following, in-context learning, and preference-based alignment into what has traditionally been a supervised…

Computation and Language · Computer Science 2026-04-29 Baban Gain , Dibyanayan Bandyopadhyay , Asif Ekbal , Trilok Nath Singh

Algorithm design is crucial for effective problem-solving across various domains. The advent of Large Language Models (LLMs) has notably enhanced the automation and innovation within this field, offering new perspectives and promising…

Machine Learning · Computer Science 2026-01-06 Fei Liu , Yiming Yao , Ping Guo , Zhiyuan Yang , Zhe Zhao , Xi Lin , Xialiang Tong , Kun Mao , Zhichao Lu , Zhenkun Wang , Mingxuan Yuan , Qingfu Zhang