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相关论文: Leveraging ChatGPT in Pharmacovigilance Event Extr…

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Event extraction is a fundamental task in natural language processing that involves identifying and extracting information about events mentioned in text. However, it is a challenging task due to the lack of annotated data, which is…

计算与语言 · 计算机科学 2023-03-10 Jun Gao , Huan Zhao , Changlong Yu , Ruifeng Xu

The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently. However, their evaluation in the benchmark academic datasets remains under-explored due to the difficulty of evaluating the generative…

Large Language Models (LLMs) like ChatGPT have demonstrated amazing capabilities in comprehending user intents and generate reasonable and useful responses. Beside their ability to chat, their capabilities in various natural language…

计算与语言 · 计算机科学 2026-02-12 Liz Li , Wei Zhu

Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on…

分布式、并行与集群计算 · 计算机科学 2024-07-09 Mario Sänger , Ninon De Mecquenem , Katarzyna Ewa Lewińska , Vasilis Bountris , Fabian Lehmann , Ulf Leser , Thomas Kosch

Recent advancements in large language models (LLMs) have led to the development of highly potent models like OpenAI's ChatGPT. These models have exhibited exceptional performance in a variety of tasks, such as question answering, essay…

计算与语言 · 计算机科学 2023-04-12 Ruixiang Tang , Xiaotian Han , Xiaoqian Jiang , Xia Hu

Recent development of large language models (LLMs), such as ChatGPT has been widely applied to a wide range of software engineering tasks. Many papers have reported their analysis on the potential advantages and limitations of ChatGPT for…

软件工程 · 计算机科学 2023-09-18 Priyanka Mudgal , Rita Wouhaybi

ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and…

Participant recruitment based on unstructured medical texts such as clinical notes and radiology reports has been a challenging yet important task for the cohort establishment in clinical research. Recently, Large Language Models (LLMs)…

计算与语言 · 计算机科学 2023-07-24 Zihan Guan , Zihao Wu , Zhengliang Liu , Dufan Wu , Hui Ren , Quanzheng Li , Xiang Li , Ninghao Liu

ChatGPT, as a recently launched large language model (LLM), has shown superior performance in various natural language processing (NLP) tasks. However, two major limitations hinder its potential applications: (1) the inflexibility of…

计算与语言 · 计算机科学 2023-09-20 Yucheng Shi , Hehuan Ma , Wenliang Zhong , Qiaoyu Tan , Gengchen Mai , Xiang Li , Tianming Liu , Junzhou Huang

The capability of Large Language Models (LLMs) like ChatGPT to comprehend user intent and provide reasonable responses has made them extremely popular lately. In this paper, we focus on assessing the overall ability of ChatGPT using 7…

计算与语言 · 计算机科学 2023-04-25 Bo Li , Gexiang Fang , Yang Yang , Quansen Wang , Wei Ye , Wen Zhao , Shikun Zhang

Artificial Intelligence (AI) advancements have enabled the development of Large Language Models (LLMs) that can perform a variety of tasks with remarkable semantic understanding and accuracy. ChatGPT is one such LLM that has gained…

软件工程 · 计算机科学 2024-08-02 M. Mehdi Kholoosi , M. Ali Babar , Roland Croft

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…

The identification of key factors such as medications, diseases, and relationships within electronic health records and clinical notes has a wide range of applications in the clinical field. In the N2C2 2022 competitions, various tasks were…

计算与语言 · 计算机科学 2023-06-14 Shouvon Sarker , Lijun Qian , Xishuang Dong

The proliferation of Large Language Models (LLMs), such as ChatGPT, has raised concerns about their potential impact on academic integrity, prompting the need for LLM-resistant exam designs. This article investigates the performance of LLMs…

计算与语言 · 计算机科学 2023-04-25 Simon kaare Larsen

Large language models (LLMs), such as ChatGPT, have received substantial attention due to their capabilities for understanding and generating human language. While there has been a burgeoning trend in research focusing on the employment of…

Text summarization has been a crucial problem in natural language processing (NLP) for several decades. It aims to condense lengthy documents into shorter versions while retaining the most critical information. Various methods have been…

计算与语言 · 计算机科学 2023-02-17 Xianjun Yang , Yan Li , Xinlu Zhang , Haifeng Chen , Wei Cheng

Extractive summarization is a crucial task in natural language processing that aims to condense long documents into shorter versions by directly extracting sentences. The recent introduction of large language models has attracted…

计算与语言 · 计算机科学 2023-10-11 Haopeng Zhang , Xiao Liu , Jiawei Zhang

Large Language Models (LLMs) are frequently discussed in academia and the general public as support tools for virtually any use case that relies on the production of text, including software engineering. Currently there is much debate, but…

软件工程 · 计算机科学 2024-05-22 Ranim Khojah , Mazen Mohamad , Philipp Leitner , Francisco Gomes de Oliveira Neto

In this study, we present EventRL, a reinforcement learning approach developed to enhance event extraction for large language models (LLMs). EventRL utilizes outcome supervision with specific reward functions to tackle prevalent challenges…

计算与语言 · 计算机科学 2024-02-20 Jun Gao , Huan Zhao , Wei Wang , Changlong Yu , Ruifeng Xu

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.…

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