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Automatic text summarization (ATS) is an emerging technology to assist clinicians in providing continuous and coordinated care. This study presents an approach to summarize doctor-patient dialogues using generative large language models…

Computation and Language · Computer Science 2024-03-21 Mengxian Lyu , Cheng Peng , Xiaohan Li , Patrick Balian , Jiang Bian , Yonghui Wu

Large Language Models (LLMs) like the GPT and LLaMA families have demonstrated exceptional capabilities in capturing and condensing critical contextual information and achieving state-of-the-art performance in the summarization task.…

Computation and Language · Computer Science 2023-11-06 Prakamya Mishra , Zonghai Yao , Shuwei Chen , Beining Wang , Rohan Mittal , Hong Yu

Large language models (LLMs) have demonstrated impressive impact in the field of natural language processing, but they still struggle with several issues regarding, such as completeness, timeliness, faithfulness and adaptability. While…

Computation and Language · Computer Science 2023-08-24 Xintao Wang , Qianwen Yang , Yongting Qiu , Jiaqing Liang , Qianyu He , Zhouhong Gu , Yanghua Xiao , Wei Wang

Generative AI and misinformation research has evolved since our 2024 survey. This paper presents an updated perspective, transitioning from literature review to practical countermeasures. We report on changes in the threat landscape,…

Computers and Society · Computer Science 2026-02-12 Alexander Loth , Martin Kappes , Marc-Oliver Pahl

The rise of large language models (LLMs) had a transformative impact on search, ushering in a new era of search engines that are capable of generating search results in natural language text, imbued with citations for supporting sources.…

Computation and Language · Computer Science 2023-08-01 Ehsan Kamalloo , Aref Jafari , Xinyu Zhang , Nandan Thakur , Jimmy Lin

In this study, we introduce PharmacyGPT, a novel framework to assess the capabilities of large language models (LLMs) such as ChatGPT and GPT-4 in emulating the role of clinical pharmacists. Our methodology encompasses the utilization of…

Data annotation and synthesis generally refers to the labeling or generating of raw data with relevant information, which could be used for improving the efficacy of machine learning models. The process, however, is labor-intensive and…

Computation and Language · Computer Science 2024-12-04 Zhen Tan , Dawei Li , Song Wang , Alimohammad Beigi , Bohan Jiang , Amrita Bhattacharjee , Mansooreh Karami , Jundong Li , Lu Cheng , Huan Liu

Large Language Models (LLMs) employ three popular training approaches: Masked Language Models (MLM), Causal Language Models (CLM), and Sequence-to-Sequence Models (seq2seq). However, each approach has its strengths and limitations, and…

Machine Learning · Computer Science 2025-02-18 Xuefeng Liu , Songhao Jiang , Bo Li , Rick Stevens

Medical Large Vision-Language Models (Med-LVLMs) demonstrate significant potential in healthcare, but their reliance on general medical data and coarse-grained global visual understanding limits them in intelligent ophthalmic diagnosis.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Sijing Li , Tianwei Lin , Lingshuai Lin , Wenqiao Zhang , Jiang Liu , Xiaoda Yang , Juncheng Li , Yucheng He , Xiaohui Song , Jun Xiao , Yueting Zhuang , Beng Chin Ooi

Large language models (LLMs) have created new opportunities to enhance the efficiency of scholarly activities; however, challenges persist in the ethical deployment of AI assistance, including (1) the trustworthiness of AI-generated…

Computation and Language · Computer Science 2026-02-27 Mengze Hong , Di Jiang , Chen Jason Zhang , Zichang Guo , Yawen Li , Jun Chen , Shaobo Cui , Zhiyang Su

The integration of AI in education offers significant potential to enhance learning efficiency. Large Language Models (LLMs), such as ChatGPT, Gemini, and Llama, allow students to query a wide range of topics, providing unprecedented…

Information Retrieval · Computer Science 2025-04-29 Zhaoxing Li , Vahid Yazdanpanah , Jindi Wang , Wen Gu , Lei Shi , Alexandra I. Cristea , Sarah Kiden , Sebastian Stein

As world knowledge advances and new task schemas emerge, Continual Learning (CL) becomes essential for keeping Large Language Models (LLMs) current and addressing their shortcomings. This process typically involves continual instruction…

Machine Learning · Computer Science 2024-12-17 Haokun Zhao , Haixia Han , Jie Shi , Chengyu Du , Jiaqing Liang , Yanghua Xiao

The remarkable capabilities and intricate nature of Artificial Intelligence (AI) have dramatically escalated the imperative for specialized AI accelerators. Nonetheless, designing these accelerators for various AI workloads remains both…

Machine Learning · Computer Science 2025-01-07 Yonggan Fu , Yongan Zhang , Zhongzhi Yu , Sixu Li , Zhifan Ye , Chaojian Li , Cheng Wan , Yingyan Celine Lin

Genome annotation is essential for understanding the functional elements within genomes. While automated methods are indispensable for processing large-scale genomic data, they often face challenges in accurately predicting gene structures…

Genomics · Quantitative Biology 2025-04-01 Xiaomei Li , Alex Whan , Meredith McNeil , David Starns , Jessica Irons , Samuel C. Andrew , Rad Suchecki

Emerging topics in biomedical research are continuously expanding, providing a wealth of information about genes and their function. This rapid proliferation of knowledge presents unprecedented opportunities for scientific discovery and…

Genomics · Quantitative Biology 2024-12-25 Zhijian Chen , Chuan Hu , Min Wu , Qingqing Long , Xuezhi Wang , Yuanchun Zhou , Meng Xiao

The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in medical advice.…

Computation and Language · Computer Science 2023-06-27 Yunxiang Li , Zihan Li , Kai Zhang , Ruilong Dan , Steve Jiang , You Zhang

The launch of ChatGPT by OpenAI in November 2022 marked a pivotal moment for Artificial Intelligence, introducing Large Language Models (LLMs) to the mainstream and setting new records in user adoption. LLMs, particularly ChatGPT, trained…

Computation and Language · Computer Science 2024-03-18 Christian A. Schiller

The recent success of Large Language Models (LLMs) has sparked concerns about their potential to spread misinformation. As a result, there is a pressing need for tools to identify ``fake arguments'' generated by such models. To create these…

Applications of large language models (LLMs) like ChatGPT have potential to enhance clinical decision support through conversational interfaces. However, challenges of human-algorithmic interaction and clinician trust are poorly understood.…

The advancement in generative AI could be boosted with more accessible mathematics. Beyond human-AI chat, large language models (LLMs) are emerging in programming, algorithm discovery, and theorem proving, yet their genomics application is…

Other Quantitative Biology · Quantitative Biology 2023-07-07 Melanie Swan , Takashi Kido , Eric Roland , Renato P. dos Santos