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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…

Large language models (LLMs) have demonstrated remarkable capabilities across a broad spectrum of tasks. They have attracted significant attention and been deployed in numerous downstream applications. Nevertheless, akin to a double-edged…

Computation and Language · Computer Science 2023-11-28 Zishan Guo , Renren Jin , Chuang Liu , Yufei Huang , Dan Shi , Supryadi , Linhao Yu , Yan Liu , Jiaxuan Li , Bojian Xiong , Deyi Xiong

Human decision-making belongs to the foundation of our society and civilization, but we are on the verge of a future where much of it will be delegated to artificial intelligence. The arrival of Large Language Models (LLMs) has transformed…

Artificial Intelligence · Computer Science 2025-06-23 Hao Li , Gengrui Zhang , Petter Holme , Shuyue Hu , Zhen Wang

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

Computation and Language · Computer Science 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Large language models (LLMs) with billions of parameters and pretrained on massive amounts of data are now capable of near or better than state-of-the-art performance in a variety of downstream natural language processing tasks. Neural…

Computation and Language · Computer Science 2024-07-08 Victor Agostinelli , Max Wild , Matthew Raffel , Kazi Ahmed Asif Fuad , Lizhong Chen

Nowadays, pretrained language models (PLMs) have dominated the majority of NLP tasks. While, little research has been conducted on systematically evaluating the language abilities of PLMs. In this paper, we present a large-scale empirical…

Computation and Language · Computer Science 2022-05-04 Junyi Li , Tianyi Tang , Zheng Gong , Lixin Yang , Zhuohao Yu , Zhipeng Chen , Jingyuan Wang , Wayne Xin Zhao , Ji-Rong Wen

Large Language Models (LLMs) are transforming artificial intelligence, enabling autonomous agents to perform diverse tasks across various domains. These agents, proficient in human-like text comprehension and generation, have the potential…

Artificial Intelligence · Computer Science 2024-04-10 Saikat Barua

Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs), built upon LLMs, have demonstrated impressive potential in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Tao Yu , Yi-Fan Zhang , Chaoyou Fu , Junkang Wu , Jinda Lu , Kun Wang , Xingyu Lu , Yunhang Shen , Guibin Zhang , Dingjie Song , Yibo Yan , Tianlong Xu , Qingsong Wen , Zhang Zhang , Yan Huang , Liang Wang , Tieniu Tan

Large Language Models (LLMs) have reshaped our world with significant advancements in science, engineering, and society through applications ranging from scientific discoveries and medical diagnostics to Chatbots. Despite their ubiquity and…

Artificial Intelligence · Computer Science 2025-08-26 Kushal Raj Bhandari , Pin-Yu Chen , Jianxi Gao

Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have made significant advancements in reasoning capabilities. However, they still face challenges such as high computational demands and privacy concerns. This paper…

With the rapid development of large language models (LLMs), which possess powerful natural language processing and generation capabilities, LLMs are poised to provide more natural and personalized user experiences. Their deployment on…

Artificial Intelligence · Computer Science 2026-03-03 Lianjun Liu , Hongli An , Pengxuan Chen , Longxiang Ye

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their…

Computation and Language · Computer Science 2024-01-01 Yupeng Chang , Xu Wang , Jindong Wang , Yuan Wu , Linyi Yang , Kaijie Zhu , Hao Chen , Xiaoyuan Yi , Cunxiang Wang , Yidong Wang , Wei Ye , Yue Zhang , Yi Chang , Philip S. Yu , Qiang Yang , Xing Xie

Language models have gained significant interest due to their general-purpose capabilities, which appear to emerge as models are scaled to increasingly larger parameter sizes. However, these large models impose stringent requirements on…

Machine Learning · Computer Science 2024-12-23 Savitha Viswanadh Kandala , Pramuka Medaranga , Ambuj Varshney

In many scientific fields, large language models (LLMs) have revolutionized the way text and other modalities of data (e.g., molecules and proteins) are handled, achieving superior performance in various applications and augmenting the…

Computation and Language · Computer Science 2024-10-01 Yu Zhang , Xiusi Chen , Bowen Jin , Sheng Wang , Shuiwang Ji , Wei Wang , Jiawei Han

This paper explores the advancements in making large language models (LLMs) more human-like. We focus on techniques that enhance natural language understanding, conversational coherence, and emotional intelligence in AI systems. The study…

Computation and Language · Computer Science 2026-02-03 Ethem Yağız Çalık , Talha Rüzgar Akkuş

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable capability to provide proficient responses to free-text queries, demonstrating a…

Computation and Language · Computer Science 2024-07-09 Zabir Al Nazi , Wei Peng

Large Language Models (LLMs) have the potential to semi-automate some process mining (PM) analyses. While commercial models are already adequate for many analytics tasks, the competitive level of open-source LLMs in PM tasks is unknown. In…

Computation and Language · Computer Science 2024-07-19 Alessandro Berti , Humam Kourani , Wil M. P. van der Aalst

Despite the advancements of open-source large language models (LLMs), e.g., LLaMA, they remain significantly limited in tool-use capabilities, i.e., using external tools (APIs) to fulfill human instructions. The reason is that current…

The emergence of Large Language Models (LLMs) has fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational systems to scientific exploration. However, their pre-trained…

Language models (LMs) have demonstrated remarkable capabilities in NLP, yet adapting them efficiently and robustly to specific tasks remains challenging. As their scale and complexity grow, fine-tuning LMs on labelled data often…

Computation and Language · Computer Science 2025-06-27 Zhengyan Shi
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