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Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a…

The startling success of ChatGPT and other large language models (LLMs) using transformer-based generative neural network architecture in applications such as natural language processing and image synthesis has many researchers excited…

人工智能 · 计算机科学 2024-11-05 Venkat Venkatasubramanian , Arijit Chakraborty

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

This study investigates the application effectiveness of the Large Language Model (LLMs) ChatGLM in the automated generation of high school information technology exam questions. Through meticulously designed prompt engineering strategies,…

计算机与社会 · 计算机科学 2024-08-22 Yanxin Chen , Ling He

Large language models (LLMs) have emerged as versatile tools in various daily applications. However, they are fraught with issues that undermine their utility and trustworthiness. These include the incorporation of erroneous references…

计算与语言 · 计算机科学 2023-09-13 Dongyub Lee , Taesun Whang , Chanhee Lee , Heuiseok Lim

Introduction: Large language models (LLMs) can process requests and generate texts, but their feasibility for assessing complex academic content needs further investigation. To explore LLM's potential in assisting scientific review, this…

计算与语言 · 计算机科学 2026-01-29 Yinuo Liu , Emre Sezgin , Eric A. Youngstrom

Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and…

计算与语言 · 计算机科学 2025-03-25 Shervin Minaee , Tomas Mikolov , Narjes Nikzad , Meysam Chenaghlu , Richard Socher , Xavier Amatriain , Jianfeng Gao

Large Language Models (LLMs) are rapidly reshaping information retrieval by enabling interactive, generative, and inference-driven search. While traditional keyword-based search remains central to web and academic information access, it…

信息检索 · 计算机科学 2025-12-02 Zhitong Guan , Yi Wang

Verifiable generation aims to let the large language model (LLM) generate text with supporting documents, which enables the user to flexibly verify the answer and makes the LLM's output more reliable. Retrieval plays a crucial role in…

计算与语言 · 计算机科学 2024-03-28 Xiaonan Li , Changtai Zhu , Linyang Li , Zhangyue Yin , Tianxiang Sun , Xipeng Qiu

Retrieval augmentation is critical when Language Models (LMs) exploit non-parametric knowledge related to the query through external knowledge bases before reasoning. The retrieved information is incorporated into LMs as context alongside…

信息检索 · 计算机科学 2024-11-21 Mingzhu Wang , Yuzhe Zhang , Qihang Zhao , Junyi Yang , Hong Zhang

Large language models (LLMs), such as ChatGPT and Copilot, are transforming software development by automating code generation and, arguably, enable rapid prototyping, support education, and boost productivity. Therefore, correctness and…

Large language models (LLM) not only have revolutionized the field of natural language processing (NLP) but also have the potential to reshape many other fields, e.g., recommender systems (RS). However, most of the related work treats an…

信息检索 · 计算机科学 2024-03-26 Lei Li , Yongfeng Zhang , Dugang Liu , Li Chen

This paper introduces a system that integrates large language models (LLMs) into the clinical trial retrieval process, enhancing the effectiveness of matching patients with eligible trials while maintaining information privacy and allowing…

信息检索 · 计算机科学 2024-11-01 Georgios Peikos , Pranav Kasela , Gabriella Pasi

Lab results are often confusing and hard to understand. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. We aim to assess the feasibility of using LLMs to generate…

计算与语言 · 计算机科学 2024-04-23 Zhe He , Balu Bhasuran , Qiao Jin , Shubo Tian , Karim Hanna , Cindy Shavor , Lisbeth Garcia Arguello , Patrick Murray , Zhiyong Lu

Large Language Models (LLMs) excel in data synthesis but can be inaccurate in domain-specific tasks, which retrieval-augmented generation (RAG) systems address by leveraging user-provided data. However, RAGs require optimization in both…

计算与语言 · 计算机科学 2024-11-05 Kazi Ahmed Asif Fuad , Lizhong Chen

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…

Complementing natural language (NL) requirements with graphical models can improve stakeholders' communication and provide directions for system design. However, creating models from requirements involves manual effort. The advent of…

软件工程 · 计算机科学 2024-07-02 Alessio Ferrari , Sallam Abualhaija , Chetan Arora

In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities…

计算与语言 · 计算机科学 2024-03-22 Hanieh Alipour , Nick Pendar , Kohinoor Roy

In this paper, we investigate the use of large language models (LLMs) like ChatGPT for document-grounded response generation in the context of information-seeking dialogues. For evaluation, we use the MultiDoc2Dial corpus of task-oriented…

计算与语言 · 计算机科学 2023-09-22 Norbert Braunschweiler , Rama Doddipatla , Simon Keizer , Svetlana Stoyanchev

Large Language Models (LLMs) have transformed how people interact with artificial intelligence (AI) systems, achieving state-of-the-art results in various tasks, including scientific discovery and hypothesis generation. However, the lack of…

计算与语言 · 计算机科学 2024-11-06 Sikun Guo , Amir Hassan Shariatmadari , Guangzhi Xiong , Albert Huang , Eric Xie , Stefan Bekiranov , Aidong Zhang