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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

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generation capabilities. Despite their remarkable performance, LLMs…

Artificial Intelligence · Computer Science 2024-12-10 Yedi Zhang , Yufan Cai , Xinyue Zuo , Xiaokun Luan , Kailong Wang , Zhe Hou , Yifan Zhang , Zhiyuan Wei , Meng Sun , Jun Sun , Jing Sun , Jin Song Dong

Large language models (LLMs) have significantly advanced the field of natural language processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of applications. However, directly applying LLMs to solve…

With recent Nobel Prizes recognising AI contributions to science, Large Language Models (LLMs) are transforming scientific research by enhancing productivity and reshaping the scientific method. LLMs are now involved in experimental design,…

Text embedding has become a foundational technology in natural language processing (NLP) during the deep learning era, driving advancements across a wide array of downstream tasks. While many natural language understanding challenges can…

Computation and Language · Computer Science 2025-10-22 Zhijie Nie , Zhangchi Feng , Mingxin Li , Cunwang Zhang , Yanzhao Zhang , Dingkun Long , Richong Zhang

The advent of Large Language Models (LLMs) has ushered in a new era for design science in Information Systems, demanding a paradigm shift in tailoring LLMs design for business contexts. We propose and test a novel framework to customize…

Computers and Society · Computer Science 2024-05-15 Wen Wang , Zhenyue Zhao , Tianshu Sun

Recent advances in the intrinsic reasoning capabilities of large language models (LLMs) have given rise to LLM-based agent systems that exhibit near-human performance on a variety of automated tasks. However, although these systems share…

Artificial Intelligence · Computer Science 2025-08-26 Bingxi Zhao , Lin Geng Foo , Ping Hu , Christian Theobalt , Hossein Rahmani , Jun Liu

Significant efforts has been made to expand the use of Large Language Models (LLMs) beyond basic language tasks. While the generalizability and versatility of LLMs have enabled widespread adoption, evolving demands in application…

Software Engineering · Computer Science 2024-11-20 Dawen Zhang , Xiwei Xu , Chen Wang , Zhenchang Xing , Robert Mao

Large language models (LLMs) have demonstrated emergent abilities in text generation, question answering, and reasoning, facilitating various tasks and domains. Despite their proficiency in various tasks, LLMs like PaLM 540B and Llama-3.1…

Computation and Language · Computer Science 2024-12-31 Fali Wang , Zhiwei Zhang , Xianren Zhang , Zongyu Wu , Tzuhao Mo , Qiuhao Lu , Wanjing Wang , Rui Li , Junjie Xu , Xianfeng Tang , Qi He , Yao Ma , Ming Huang , Suhang Wang

The advancement of large language models (LLMs) has outpaced traditional evaluation methodologies. This progress presents novel challenges, such as measuring human-like psychological constructs, moving beyond static and task-specific…

Computation and Language · Computer Science 2026-03-12 Haoran Ye , Jing Jin , Yuhang Xie , Xin Zhang , Guojie Song

Large language models (LLMs) have substantially advanced machine learning research, including natural language processing, computer vision, data mining, etc., yet they still exhibit critical limitations in explainability, reliability,…

Machine Learning · Computer Science 2025-09-19 Xin Wang , Haoyang Li , Haibo Chen , Zeyang Zhang , Wenwu Zhu

Survey research has a long-standing history of being a human-powered field, but one that embraces various technologies for the collection, processing, and analysis of various behavioral, political, and social outcomes of interest, among…

Digital Libraries · Computer Science 2025-09-04 Trent D. Buskirk , Florian Keusch , Leah von der Heyde , Adam Eck

Large Language Models (LLMs) have transformed natural language processing and hold growing promise for advancing science, healthcare, and decision-making. Yet their training paradigms remain dominated by affirmation-based inference, akin to…

Artificial Intelligence · Computer Science 2025-12-05 Peter B. Walker , Hannah Davidson , Aiden Foster , Matthew Lienert , Thomas Pardue , Dale Russell

Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive…

Information Retrieval · Computer Science 2024-06-19 Likang Wu , Zhi Zheng , Zhaopeng Qiu , Hao Wang , Hongchao Gu , Tingjia Shen , Chuan Qin , Chen Zhu , Hengshu Zhu , Qi Liu , Hui Xiong , Enhong Chen

Large language models (LLMs) have revolutionized natural language processing with their exceptional understanding, synthesizing, and reasoning capabilities. However, deploying LLMs on resource-constrained edge devices presents significant…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-25 Yue Zheng , Yuhao Chen , Bin Qian , Xiufang Shi , Yuanchao Shu , Jiming Chen

Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite their significance, these languages face critical challenges, including data scarcity and…

Large language models (LLMs) have ushered in a new era for processing complex information in various fields, including science. The increasing amount of scientific literature allows these models to acquire and understand scientific…

Computation and Language · Computer Science 2024-08-21 Huy Quoc To , Ming Liu , Guangyan Huang

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…

The advent of Large Language Models (LLMs) has provided unprecedented capabilities for analyzing unstructured text data. However, deploying these models as reliable, robust, and scalable classifiers in production environments presents…

Computation and Language · Computer Science 2025-08-25 Doohee You , Andy Parisi , Zach Vander Velden , Lara Dantas Inojosa

With generative artificial intelligence (AI), particularly large language models (LLMs), continuing to make inroads in healthcare, it is critical to supplement traditional automated evaluations with human evaluations. Understanding and…

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