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Specialized clinical AI assistants are rapidly entering medical practice, often framed as safer or more reliable than general-purpose large language models (LLMs). Yet, unlike frontier models, these clinical tools are rarely subjected to…

With the advancement of Artificial Intelligence (AI) and Large Language Models (LLMs), there is a profound transformation occurring in the realm of natural language processing tasks within the legal domain. The capabilities of LLMs are…

计算与语言 · 计算机科学 2024-04-02 Weicong Qin , Zhongxiang Sun

With the rapid development of large language models (LLMs), which possess powerful natural language processing and generation capabilities, LLMs are poised to provide more natural and personalized user experiences. Their deployment on…

人工智能 · 计算机科学 2026-03-03 Lianjun Liu , Hongli An , Pengxuan Chen , Longxiang Ye

Ableist language perpetuates harmful stereotypes and exclusion, yet its nuanced nature makes it difficult to recognize and address. Artificial intelligence could serve as a powerful ally in the fight against ableist language, offering tools…

人机交互 · 计算机科学 2026-02-24 Kynnedy Simone Smith , Lydia B. Chilton , Danielle Bragg

Large Language Models (LLMs) have fundamentally transformed approaches to Natural Language Processing (NLP) tasks across diverse domains. In healthcare, accurate and cost-efficient text classification is crucial, whether for clinical notes…

计算与语言 · 计算机科学 2026-02-16 Hajar Sakai , Sarah S. Lam

Large Language Models (LLMs) have remarkable capabilities across NLP tasks. However, their performance in multilingual contexts, especially within the mental health domain, has not been thoroughly explored. In this paper, we evaluate…

计算与语言 · 计算机科学 2026-02-03 Nishat Raihan , Sadiya Sayara Chowdhury Puspo , Ana-Maria Bucur , Stevie Chancellor , Marcos Zampieri

With the introduction of ChatGPT, Large Language Models (LLMs) have received enormous attention in healthcare. Despite their potential benefits, researchers have underscored various ethical implications. While individual instances have…

计算机与社会 · 计算机科学 2024-07-09 Joschka Haltaufderheide , Robert Ranisch

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

计算与语言 · 计算机科学 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

Background: Recent advancements in large language models (LLMs) offer potential benefits in healthcare, particularly in processing extensive patient records. However, existing benchmarks do not fully assess LLMs' capability in handling…

Linguistically inclusive LLMs -- which maintain good performance regardless of the language with which they are prompted -- are necessary for the diffusion of AI benefits around the world. Multilingual jailbreaks that rely on language…

计算与语言 · 计算机科学 2024-10-30 Artūrs Kanepajs , Vladimir Ivanov , Richard Moulange

Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evaluating equity-related model failures is a critical step toward…

Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase…

人机交互 · 计算机科学 2025-03-24 Michelle Brachman , Amina El-Ashry , Casey Dugan , Werner Geyer

Large Language Models (LLMs), AI-driven models that can achieve general-purpose language understanding and generation, have emerged as a transformative force, revolutionizing fields well beyond Natural Language Processing (NLP) and…

信息论 · 计算机科学 2024-02-27 Ali Maatouk , Nicola Piovesan , Fadhel Ayed , Antonio De Domenico , Merouane Debbah

The widespread adoption of large language models (LLMs) across diverse AI applications is proof of the outstanding achievements obtained in several tasks, such as text mining, text generation, and question answering. However, LLMs are not…

计算与语言 · 计算机科学 2023-11-15 Alessandro Bruno , Pier Luigi Mazzeo , Aladine Chetouani , Marouane Tliba , Mohamed Amine Kerkouri

While many researchers use Large Language Models (LLMs) through chat-based access, their real potential lies in leveraging LLMs via application programming interfaces (APIs). This paper conceptualizes LLMs as universal text processing…

计算与语言 · 计算机科学 2026-03-23 Ivan Zupic

Large Language Models(LLMs)have become effective tools for natural language processing and have been used in many different fields. This essay offers a succinct summary of various LLM subcategories. The survey emphasizes recent developments…

计算与语言 · 计算机科学 2023-07-21 Saurabh Pahune , Manoj Chandrasekharan

Artificial intelligence (AI) has shown the potential to revolutionize healthcare by improving diagnostic accuracy, optimizing workflows, and personalizing treatment plans. Large Language Models (LLMs) and Multimodal Large Language Models…

Generative AI tools, particularly those utilizing large language models (LLMs), are increasingly used in everyday contexts. While these tools enhance productivity and accessibility, little is known about how Deaf and Hard of Hearing (DHH)…

人机交互 · 计算机科学 2025-01-23 Shuxu Huffman , Si Chen , Kelly Avery Mack , Haotian Su , Qi Wang , Raja Kushalnagar

Recent advancements in Large Language Models (LLMs), such as ChatGPT and LLaMA, have significantly transformed Natural Language Processing (NLP) with their outstanding abilities in text generation, summarization, and classification.…

计算与语言 · 计算机科学 2024-08-12 Md Nazmus Sakib , Md Athikul Islam , Royal Pathak , Md Mashrur Arifin

Large Language Models (LLMs) have significantly advanced the development of Legal Artificial Intelligence (Legal AI) in recent years, enhancing the efficiency and accuracy of legal tasks. To advance research and applications of LLM-based…

计算与语言 · 计算机科学 2025-09-15 Zhitian Hou , Zihan Ye , Nanli Zeng , Tianyong Hao , Kun Zeng
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