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相关论文: Arabic Dataset for LLM Safeguard Evaluation

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Many studies have demonstrated that large language models (LLMs) can produce harmful responses, exposing users to unexpected risks when LLMs are deployed. Previous studies have proposed comprehensive taxonomies of the risks posed by LLMs,…

计算与语言 · 计算机科学 2024-08-06 Yuxia Wang , Zenan Zhai , Haonan Li , Xudong Han , Lizhi Lin , Zhenxuan Zhang , Jingru Zhao , Preslav Nakov , Timothy Baldwin

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

Studying the robustness of Large Language Models (LLMs) to unsafe behaviors is an important topic of research today. Building safety classification models or guard models, which are fine-tuned models for input/output safety classification…

计算与语言 · 计算机科学 2025-07-30 Sowmya Vajjala

The last two years have seen a rapid growth in concerns around the safety of large language models (LLMs). Researchers and practitioners have met these concerns by creating an abundance of datasets for evaluating and improving LLM safety.…

计算与语言 · 计算机科学 2025-01-13 Paul Röttger , Fabio Pernisi , Bertie Vidgen , Dirk Hovy

Over the past three years, the rapid advancement of Large Language Models (LLMs) has had a profound impact on multiple areas of Artificial Intelligence (AI), particularly in Natural Language Processing (NLP) across diverse languages,…

计算与语言 · 计算机科学 2025-05-14 Haneh Rhel , Dmitri Roussinov

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

This survey offers a comprehensive overview of Large Language Models (LLMs) designed for Arabic language and its dialects. It covers key architectures, including encoder-only, decoder-only, and encoder-decoder models, along with the…

计算与语言 · 计算机科学 2026-05-20 Malak Mashaabi , Shahad Al-Khalifa , Hend Al-Khalifa

Large Language Models (LLMs) have shown remarkable capabilities, not only in generating human-like text, but also in acquiring knowledge. This highlights the need to go beyond the typical Natural Language Processing downstream benchmarks…

The rapid advancements in Large Language Models (LLMs) have led to significant improvements in various natural language processing tasks. However, the evaluation of LLMs' legal knowledge, particularly in non-English languages such as…

The widespread adoption and increasing prominence of large language models (LLMs) in global technologies necessitate a rigorous focus on ensuring their safety across a diverse range of linguistic and cultural contexts. The lack of a…

计算与语言 · 计算机科学 2025-08-28 Zhiyuan Ning , Tianle Gu , Jiaxin Song , Shixin Hong , Lingyu Li , Huacan Liu , Jie Li , Yixu Wang , Meng Lingyu , Yan Teng , Yingchun Wang

Large Language Models (LLMs) are now commonplace in conversation applications. However, their risks of misuse for generating harmful responses have raised serious societal concerns and spurred recent research on LLM conversation safety.…

计算与语言 · 计算机科学 2024-03-28 Zhichen Dong , Zhanhui Zhou , Chao Yang , Jing Shao , Yu Qiao

Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum of tasks, revolutionizing how we approach language understanding and generations.…

密码学与安全 · 计算机科学 2025-06-13 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He , Erfan Shayegani

Large Language Models (LLMs) are acquiring a wider range of capabilities, including understanding and responding in multiple languages. While they undergo safety training to prevent them from answering illegal questions, imbalances in…

计算与语言 · 计算机科学 2025-03-18 Likai Tang , Niruth Bogahawatta , Yasod Ginige , Jiarui Xu , Shixuan Sun , Surangika Ranathunga , Suranga Seneviratne

The detection of toxic language in the Arabic language has emerged as an active area of research in recent years, and reviewing the existing datasets employed for training the developed solutions has become a pressing need. This paper…

计算与语言 · 计算机科学 2024-01-31 Imene Bensalem , Paolo Rosso , Hanane Zitouni

Safety evaluation of Large Language Models (LLMs) has largely focused on high-resource languages, leaving low-resource languages critically underserved. We present AlbanianLLMSafety, the first publicly available safety evaluation dataset…

计算与语言 · 计算机科学 2026-05-29 Wajdi Zaghouani , Kholoud K. Aldous , Isra Fejzullaj

Large language models (LLMs) have demonstrated remarkable capabilities across a broad spectrum of tasks. They have attracted significant attention and been deployed in numerous downstream applications. Nevertheless, akin to a double-edged…

计算与语言 · 计算机科学 2023-11-28 Zishan Guo , Renren Jin , Chuang Liu , Yufei Huang , Dan Shi , Supryadi , Linhao Yu , Yan Liu , Jiaxuan Li , Bojian Xiong , Deyi Xiong

Recent years have witnessed a significant interest in developing large multimodal models (LMMs) capable of performing various visual reasoning and understanding tasks. This has led to the introduction of multiple LMM benchmarks to evaluate…

计算机视觉与模式识别 · 计算机科学 2024-10-25 Sara Ghaboura , Ahmed Heakl , Omkar Thawakar , Ali Alharthi , Ines Riahi , Abduljalil Saif , Jorma Laaksonen , Fahad S. Khan , Salman Khan , Rao M. Anwer

Large Language Models (LLMs) represent an advanced evolution of earlier, simpler language models. They boast enhanced abilities to handle complex language patterns and generate coherent text, images, audios, and videos. Furthermore, they…

密码学与安全 · 计算机科学 2024-03-01 Jun Huang , Jiawei Zhang , Qi Wang , Weihong Han , Yanchun Zhang

As Large Language Models (LLMs) continue to advance in understanding and generating long sequences, new safety concerns have been introduced through the long context. However, the safety of LLMs in long-context tasks remains under-explored,…

计算与语言 · 计算机科学 2025-02-25 Yida Lu , Jiale Cheng , Zhexin Zhang , Shiyao Cui , Cunxiang Wang , Xiaotao Gu , Yuxiao Dong , Jie Tang , Hongning Wang , Minlie Huang
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