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相关论文: ChatGPT for Arabic Grammatical Error Correction

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This study investigates the efficacy of large language models (LLMs) as tools for grading master-level student essays. Utilizing a sample of 60 essays in political science, the study compares the accuracy of grades suggested by the GPT-4…

综合经济学 · 经济学 2024-06-25 Magnus Lundgren

Generative Language Models (LMs) such as ChatGPT have exhibited remarkable performance across various downstream tasks. Nevertheless, one of their most prominent drawbacks is generating inaccurate or false information with a confident tone.…

计算与语言 · 计算机科学 2024-05-14 Haixia Han , Jiaqing Liang , Jie Shi , Qianyu He , Yanghua Xiao

Despite the purported multilingual proficiency of instruction-finetuned large language models (LLMs) such as ChatGPT and Bard, the linguistic inclusivity of these models remains insufficiently explored. Considering this constraint, we…

The development of medical chatbots in Arabic is significantly constrained by the scarcity of large-scale, high-quality annotated datasets. While prior efforts compiled a dataset of 20,000 Arabic patient-doctor interactions from social…

计算与语言 · 计算机科学 2025-09-15 Abdulrahman Allam , Seif Ahmed , Ali Hamdi , Khaled Shaban

Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a…

计算与语言 · 计算机科学 2024-04-02 Ankit Satpute , Noah Giessing , Andre Greiner-Petter , Moritz Schubotz , Olaf Teschke , Akiko Aizawa , Bela Gipp

Previous learning-based vulnerability detection methods relied on either medium-sized pre-trained models or smaller neural networks from scratch. Recent advancements in Large Pre-Trained Language Models (LLMs) have showcased remarkable…

软件工程 · 计算机科学 2024-01-30 Xin Zhou , Ting Zhang , David Lo

Providing effective feedback is important for student learning in programming problem-solving. In this sense, Large Language Models (LLMs) have emerged as potential tools to automate feedback generation. However, their reliability and…

软件工程 · 计算机科学 2025-03-20 Priscylla Silva , Evandro Costa

Generative large language models (LLMs) are a promising alternative to pre-trained language models for entity matching due to their high zero-shot performance and ability to generalize to unseen entities. Existing research on using LLMs for…

计算与语言 · 计算机科学 2025-05-22 Aaron Steiner , Ralph Peeters , Christian Bizer

Although rarely stated, in practice, Grammatical Error Correction (GEC) encompasses various models with distinct objectives, ranging from grammatical error detection to improving fluency. Traditional evaluation methods fail to fully capture…

计算与语言 · 计算机科学 2023-08-21 Robert Östling , Katarina Gillholm , Murathan Kurfalı , Marie Mattson , Mats Wirén

This study explores enhancing grammatical error correction (GEC) through artificial error generation (AEG) using language models (LMs). Specifically, we fine-tune Llama 2-based LMs for error generation and find that this approach yields…

计算与语言 · 计算机科学 2024-10-07 Agnes Luhtaru , Taido Purason , Martin Vainikko , Maksym Del , Mark Fishel

While large-scale language models (LLMs) have demonstrated remarkable capabilities in specific natural language processing (NLP) tasks, they may still lack proficiency compared to specialized models in certain domains, such as grammatical…

计算与语言 · 计算机科学 2024-12-18 Tao Fang , Derek F. Wong , Lusheng Zhang , Keyan Jin , Qiang Zhang , Tianjiao Li , Jinlong Hou , Lidia S. Chao

Large language models (LLMs) have been proposed as scalable tools to address the gap between the importance of individualized written feedback and the practical challenges of providing it at scale. However, concerns persist regarding the…

其他统计学 · 统计学 2025-11-12 Niklas Ippisch , Markus Herklotz , Anna-Carolina Haensch , Carsten Schwemmer

Assessing learners in ill-defined domains, such as scenario-based human tutoring training, is an area of limited research. Equity training requires a nuanced understanding of context, but do contemporary large language models (LLMs) have a…

人机交互 · 计算机科学 2025-01-14 Sanjit Kakarla , Conrad Borchers , Danielle Thomas , Shambhavi Bhushan , Kenneth R. Koedinger

This paper investigates the performance of the Large Language Models (LLMs) ChatGPT-3.5 and GPT-4 in solving introductory programming tasks. Based on the performance, implications for didactic scenarios and assessment formats utilizing LLMs…

软件工程 · 计算机科学 2023-08-21 Natalie Kiesler , Daniel Schiffner

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

人工智能 · 计算机科学 2023-09-12 Chang Liu , Bo Wu

Recent advancements in Large Language Models (LLMs) have significantly influenced the landscape of language and speech research. Despite this progress, these models lack specific benchmarking against state-of-the-art (SOTA) models tailored…

This paper studies recent developments in large language models' (LLM) abilities to pass assessments in introductory and intermediate Python programming courses at the postsecondary level. The emergence of ChatGPT resulted in heated debates…

计算机与社会 · 计算机科学 2023-10-05 Jaromir Savelka , Arav Agarwal , Marshall An , Chris Bogart , Majd Sakr

Mental health disorders pose a growing public health concern in the Arab world, emphasizing the need for accessible diagnostic and intervention tools. Large language models (LLMs) offer a promising approach, but their application in Arabic…

计算与语言 · 计算机科学 2025-01-14 Noureldin Zahran , Aya E. Fouda , Radwa J. Hanafy , Mohammed E. Fouda

In the current era of digital communication and widespread use of social media, it is crucial to develop an understanding of persuasive techniques employed in written text. This knowledge is essential for effectively discerning accurate…

计算与语言 · 计算机科学 2024-05-22 Abdurahmman Alzahrani , Eyad Babkier , Faisal Yanbaawi , Firas Yanbaawi , Hassan Alhuzali

Research suggests that tutors should adopt a strategic approach when addressing math errors made by low-efficacy students. Rather than drawing direct attention to the error, tutors should guide the students to identify and correct their…

人机交互 · 计算机科学 2024-01-09 Sanjit Kakarla , Danielle Thomas , Jionghao Lin , Shivang Gupta , Kenneth R. Koedinger