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相关论文: How well can LLMs Grade Essays in Arabic?

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The growing use of large language models (LLMs) has raised concerns regarding their safety. While many studies have focused on English, the safety of LLMs in Arabic, with its linguistic and cultural complexities, remains under-explored.…

计算与语言 · 计算机科学 2025-02-11 Yasser Ashraf , Yuxia Wang , Bin Gu , Preslav Nakov , Timothy Baldwin

The emergence of large language models (LLMs) has brought a new paradigm to automated essay scoring (AES), a long-standing and practical application of natural language processing in education. However, achieving human-level…

计算与语言 · 计算机科学 2025-09-22 Jinhee Jang , Ayoung Moon , Minkyoung Jung , YoungBin Kim , Seung Jin Lee

We aim to examine the extent to which Large Language Models (LLMs) can 'talk much' about grammar modules, providing evidence from syntax core properties translated by ChatGPT into Arabic. We collected 44 terms from generative syntax…

计算与语言 · 计算机科学 2026-04-10 Mohammed Q. Shormani , Yehia A. AlSohbani

Recent advancements in instruction fine-tuning, alignment methods such as reinforcement learning from human feedback (RLHF), and optimization techniques like direct preference optimization (DPO) have significantly enhanced the adaptability…

The performance of large language models (LLMs) is acutely sensitive to the phrasing of prompts, which raises significant concerns about their reliability in real-world scenarios. Existing studies often divide prompts into task-level…

计算与语言 · 计算机科学 2024-10-31 Bowen Cao , Deng Cai , Zhisong Zhang , Yuexian Zou , Wai Lam

This paper explores the integration of Large Language Models (LLMs) into Automatic Speech Recognition (ASR) systems to improve transcription accuracy. The increasing sophistication of LLMs, with their in-context learning capabilities and…

计算与语言 · 计算机科学 2025-06-03 Zeping Min , Jinbo Wang

In recent years, Large Language Models have revolutionized the field of natural language processing, showcasing an impressive rise predominantly in English-centric domains. These advancements have set a global benchmark, inspiring…

计算与语言 · 计算机科学 2024-05-06 Manel Aloui , Hasna Chouikhi , Ghaith Chaabane , Haithem Kchaou , Chehir Dhaouadi

Dialectal Arabic (DA) varieties are under-served by language technologies, particularly large language models (LLMs). This trend threatens to exacerbate existing social inequalities and limits LLM applications, yet the research community…

计算与语言 · 计算机科学 2025-01-07 Nathaniel R. Robinson , Shahd Abdelmoneim , Kelly Marchisio , Sebastian Ruder

Recently, Large Language Models~(LLMs) such as ChatGPT have showcased remarkable abilities in solving general tasks, demonstrating the potential for applications in recommender systems. To assess how effectively LLMs can be used in…

信息检索 · 计算机科学 2025-01-17 Lanling Xu , Junjie Zhang , Bingqian Li , Jinpeng Wang , Sheng Chen , Wayne Xin Zhao , Ji-Rong Wen

In recent years, Large Language Models (LLMs) have become widely used in medical applications, such as clinical decision support, medical education, and medical question answering. Yet, these models are often English-centric, limiting their…

计算与语言 · 计算机科学 2026-02-06 Chaimae Abouzahir , Congbo Ma , Nizar Habash , Farah E. Shamout

Large Language Models (LLMs) have demonstrated promise in medical knowledge assessments, yet their practical utility in real-world clinical decision-making remains underexplored. In this study, we evaluated the performance of three…

计算与语言 · 计算机科学 2025-12-30 Mengdi Chai , Ali R. Zomorrodi

Evaluating open-ended written examination responses from students is an essential yet time-intensive task for educators, requiring a high degree of effort, consistency, and precision. Recent developments in Large Language Models (LLMs)…

计算与语言 · 计算机科学 2024-05-10 Jussi S. Jauhiainen , Agustín Garagorry Guerra

Large language models (LLMs), renowned for their powerful conversational abilities, are widely recognized as exceptional tools in the field of education, particularly in the context of automated intelligent instruction systems for language…

计算与语言 · 计算机科学 2024-07-19 Kaiqi Fu , Linkai Peng , Nan Yang , Shuran Zhou

Automated Essay Scoring (AES) plays a crucial role in educational assessment by providing scalable and consistent evaluations of writing tasks. However, traditional AES systems face three major challenges: (1) reliance on handcrafted…

计算与语言 · 计算机科学 2025-05-21 Jiamin Su , Yibo Yan , Fangteng Fu , Han Zhang , Jingheng Ye , Xiang Liu , Jiahao Huo , Huiyu Zhou , Xuming Hu

Large language models (LLMs) have recently garnered significant interest. With in-context learning, LLMs achieve impressive results in various natural language tasks. However, the application of LLMs to sentence embeddings remains an area…

计算与语言 · 计算机科学 2023-08-01 Ting Jiang , Shaohan Huang , Zhongzhi Luan , Deqing Wang , Fuzhen Zhuang

The swift progress and widespread acceptance of artificial intelligence (AI) systems highlight a pressing requirement to comprehend both the capabilities and potential risks associated with AI. Given the linguistic complexity, cultural…

计算与语言 · 计算机科学 2024-11-06 Emad A. Alghamdi , Reem I. Masoud , Deema Alnuhait , Afnan Y. Alomairi , Ahmed Ashraf , Mohamed Zaytoon

As Large Language Models (LLMs) are increasingly deployed to generate educational content, a critical safety question arises: can these models reliably estimate the difficulty of the questions they produce? Using Brazil's high-stakes ENEM…

计算机与社会 · 计算机科学 2026-02-09 Thiago Brant , Julien Kühn , Jun Pang

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a promising approach to address some of the challenging…

This study explores the feasibility of using large language models (LLMs), specifically GPT-4o (ChatGPT), for automated grading of conceptual questions in an undergraduate Mechanical Engineering course. We compared the grading performance…

计算机与社会 · 计算机科学 2024-11-07 Rujun Gao , Xiaosu Guo , Xiaodi Li , Arun Balajiee Lekshmi Narayanan , Naveen Thomas , Arun R. Srinivasa