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Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-world clinical settings. However, clinical decision-making is inherently safety-critical,…

计算与语言 · 计算机科学 2026-04-13 Xiaohan Ren , Chenxiao Fan , Wenyin Ma , Hongliang He , Chongming Gao , Xiaoyan Zhao , Fuli Feng

Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE tasks. Nevertheless, a comprehensive understanding of the…

软件工程 · 计算机科学 2024-04-11 Xinyi Hou , Yanjie Zhao , Yue Liu , Zhou Yang , Kailong Wang , Li Li , Xiapu Luo , David Lo , John Grundy , Haoyu Wang

Large Language Models (LLMs) have gained significant attention in the medical domain for their human-level capabilities, leading to increased efforts to explore their potential in various healthcare applications. However, despite such a…

Large Language Models (LLMs) are revolutionizing bioinformatics, enabling advanced analysis of DNA, RNA, proteins, and single-cell data. This survey provides a systematic review of recent advancements, focusing on genomic sequence modeling,…

计算与语言 · 计算机科学 2026-03-03 Zhenyu Wang , Zikang Wang , Jiyue Jiang , Pengan Chen , Xiangyu Shi , Yu Li

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…

计算与语言 · 计算机科学 2024-07-08 Victor Agostinelli , Max Wild , Matthew Raffel , Kazi Ahmed Asif Fuad , Lizhong Chen

Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of general-domain tasks. However, their effectiveness in specialized fields, such as construction, remains underexplored. In this paper, we introduce…

计算与语言 · 计算机科学 2025-08-25 Yanzhao Wu , Lufan Wang , Rui Liu

Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but the quality bar for medical and clinical applications is high. Today, attempts to assess models' clinical knowledge…

Large Language Models (LLMs) have the potential of facilitating the development of Artificial Intelligence technology to assist medical experts for interactive decision support, which has been demonstrated by their competitive performances…

计算与语言 · 计算机科学 2024-11-12 Iñigo Alonso , Maite Oronoz , Rodrigo Agerri

Objectives: To evaluate the current limitations of large language models (LLMs) in medical question answering, focusing on the quality of datasets used for their evaluation. Materials and Methods: Widely-used benchmark datasets, including…

计算与语言 · 计算机科学 2025-07-15 Mahmoud Alwakeel , Aditya Nagori , Vijay Krishnamoorthy , Rishikesan Kamaleswaran

Multimodal recommender systems (MRS) integrate heterogeneous user and item data, such as text, images, and structured information, to enhance recommendation performance. The emergence of large language models (LLMs) introduces new…

信息检索 · 计算机科学 2025-05-16 Alejo Lopez-Avila , Jinhua Du

The large-scale development of large language models (LLMs) in medical contexts, such as diagnostic assistance and treatment recommendations, necessitates that these models possess accurate medical knowledge and deliver traceable…

人工智能 · 计算机科学 2025-08-12 Qiyuan Li , Haijiang Liu , Caicai Guo , Chao Gao , Deyu Chen , Meng Wang , Feng Gao , Frank van Harmelen , Jinguang Gu

Large language models (LLMs) such as GPT-4o and o1 have demonstrated strong performance on clinical natural language processing (NLP) tasks across multiple medical benchmarks. Nonetheless, two high-impact NLP tasks - structured tabular…

Large language models (LLMs) are emerging as promising tools for mental health care, offering scalable support through their ability to generate human-like responses. However, the effectiveness of these models in clinical settings remains…

人工智能 · 计算机科学 2024-08-22 Yining Hua , Hongbin Na , Zehan Li , Fenglin Liu , Xiao Fang , David Clifton , John Torous

Large language models (LLMs) show promise for improving the efficiency of qualitative analysis in large, multi-site health-services research. Yet methodological guidance for LLM integration into qualitative analysis and evidence of their…

计算与语言 · 计算机科学 2026-01-22 Sasha Ronaghi , Emma-Louise Aveling , Maria Levis , Rachel Lauren Ross , Emily Alsentzer , Sara Singer

Multimodal large language models (MLLMs) hold significant potential in medical applications, including disease diagnosis and clinical decision-making. However, these tasks require highly accurate, context-sensitive, and professionally…

计算与语言 · 计算机科学 2025-09-01 Meidan Ding , Jipeng Zhang , Wenxuan Wang , Cheng-Yi Li , Wei-Chieh Fang , Hsin-Yu Wu , Haiqin Zhong , Wenting Chen , Linlin Shen

Large Language Models (LLMs) have emerged as powerful tools for automating complex reasoning and decision-making tasks. In telecommunications, they hold the potential to transform network optimization, automate troubleshooting, enhance…

In recent years, Large Language Models (LLMs) have demonstrated an impressive ability to encode knowledge during pre-training on large text corpora. They can leverage this knowledge for downstream tasks like question answering (QA), even in…

计算与语言 · 计算机科学 2024-06-11 Juraj Vladika , Phillip Schneider , Florian Matthes

Digital health tools have the potential to significantly improve the delivery of healthcare services. However, their adoption remains comparatively limited due, in part, to challenges surrounding usability and trust. Large Language Models…

计算与语言 · 计算机科学 2024-03-01 Fergus Imrie , Paulius Rauba , Mihaela van der Schaar

Recently, Large Language Models (LLMs) have showcased remarkable capabilities in natural language understanding. While demonstrating proficiency in everyday conversations and question-answering situations, these models frequently struggle…

计算与语言 · 计算机科学 2023-08-28 Chaoyi Wu , Weixiong Lin , Xiaoman Zhang , Ya Zhang , Yanfeng Wang , Weidi Xie