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We perform a critical examination of the scientific methodology behind contemporary large language model (LLM) research. For this we assess over 2,000 research works released between 2020 and 2024 based on criteria typical of what is…

计算与语言 · 计算机科学 2025-06-03 Adrian de Wynter

Large Language Models (LLMs) have rapidly become important tools in Biomedical and Health Informatics (BHI), enabling new ways to analyze data, treat patients, and conduct research. This study aims to provide a comprehensive overview of LLM…

数字图书馆 · 计算机科学 2024-07-30 Huizi Yu , Lizhou Fan , Lingyao Li , Jiayan Zhou , Zihui Ma , Lu Xian , Wenyue Hua , Sijia He , Mingyu Jin , Yongfeng Zhang , Ashvin Gandhi , Xin Ma

Large language models (LLMs) have been applied to tasks in healthcare, ranging from medical exam questions to responding to patient questions. With increasing institutional partnerships between companies producing LLMs and healthcare…

计算与语言 · 计算机科学 2024-04-10 Jesutofunmi A. Omiye , Haiwen Gui , Shawheen J. Rezaei , James Zou , Roxana Daneshjou

The use of machine learning (ML) in health care raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of health care.…

计算机与社会 · 计算机科学 2021-07-29 Irene Y. Chen , Emma Pierson , Sherri Rose , Shalmali Joshi , Kadija Ferryman , Marzyeh Ghassemi

Large language models (LLMs) are being increasingly integrated into legal applications, including judicial decision support, legal practice assistance, and public-facing legal services. While LLMs show strong potential in handling legal…

With the advent of Large Language Models (LLMs), medical artificial intelligence (AI) has experienced substantial technological progress and paradigm shifts, highlighting the potential of LLMs to streamline healthcare delivery and improve…

计算与语言 · 计算机科学 2024-12-10 Lei Liu , Xiaoyan Yang , Junchi Lei , Yue Shen , Jian Wang , Peng Wei , Zhixuan Chu , Zhan Qin , Kui Ren

The advancement of generative AI, particularly large language models (LLMs), has a significant impact on politics and democracy, offering potential across various domains, including policymaking, political communication, analysis, and…

计算与语言 · 计算机科学 2024-12-17 Goshi Aoki

As scientific research becomes increasingly complex, innovative tools are needed to manage vast data, facilitate interdisciplinary collaboration, and accelerate discovery. Large language models (LLMs) are now evolving into LLM-based…

人工智能 · 计算机科学 2026-02-03 Shuo Ren , Can Xie , Pu Jian , Zhenjiang Ren , Chunlin Leng , Jiajun Zhang

This work provides an explanatory view of how LLMs can apply moral reasoning to both criticize and defend sexist language. We assessed eight large language models, all of which demonstrated the capability to provide explanations grounded in…

计算与语言 · 计算机科学 2024-10-02 Rongchen Guo , Isar Nejadgholi , Hillary Dawkins , Kathleen C. Fraser , Svetlana Kiritchenko

In the burgeoning field of Large Language Models (LLMs), developing a robust safety mechanism, colloquially known as "safeguards" or "guardrails", has become imperative to ensure the ethical use of LLMs within prescribed boundaries. This…

密码学与安全 · 计算机科学 2024-06-06 Yi Dong , Ronghui Mu , Yanghao Zhang , Siqi Sun , Tianle Zhang , Changshun Wu , Gaojie Jin , Yi Qi , Jinwei Hu , Jie Meng , Saddek Bensalem , Xiaowei Huang

[Context] Generative AI technologies, particularly Large Language Models (LLMs), have transformed numerous domains by enhancing convenience and efficiency in information retrieval, content generation, and decision-making processes. However,…

计算机与社会 · 计算机科学 2025-08-25 Yutan Huang , Chetan Arora , Wen Cheng Houng , Tanjila Kanij , Anuradha Madulgalla , John Grundy

Large language models (LLMs) have attracted significant attention for potential applications in digital health, while their application in mental health is subject to ongoing debate. This systematic review aims to evaluate the usage of LLMs…

计算机与社会 · 计算机科学 2024-08-14 Zhijun Guo , Alvina Lai , Johan Hilge Thygesen , Joseph Farrington , Thomas Keen , Kezhi Li

Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the advent of large language models affect the practice of…

We explore how large language models (LLMs) can be influenced by prompting them to alter their initial decisions and align them with established ethical frameworks. Our study is based on two experiments designed to assess the susceptibility…

计算与语言 · 计算机科学 2024-11-19 Allison Huang , Yulu Niki Pi , Carlos Mougan

This paper explores the advancements in making large language models (LLMs) more human-like. We focus on techniques that enhance natural language understanding, conversational coherence, and emotional intelligence in AI systems. The study…

计算与语言 · 计算机科学 2026-02-03 Ethem Yağız Çalık , Talha Rüzgar Akkuş

As AI systems increasingly navigate applications in healthcare, law, and governance, understanding how they handle ethically complex scenarios becomes critical. Previous work has mainly examined the moral judgments in large language models…

Large Language Models (LLMs) have quickly risen to prominence due to their ability to perform at or close to the state-of-the-art in a variety of fields while handling natural language. An important field of research is the application of…

密码学与安全 · 计算机科学 2024-02-28 Gabriel de Jesus Coelho da Silva , Carlos Becker Westphall

Large language models (LLMs) represent a major advance in artificial intelligence (AI) research. However, the widespread use of LLMs is also coupled with significant ethical and social challenges. Previous research has pointed towards…

计算与语言 · 计算机科学 2023-06-28 Jakob Mökander , Jonas Schuett , Hannah Rose Kirk , Luciano Floridi

We present an ethical decision-making framework that refines a pre-trained reinforcement learning (RL) model using a task-agnostic ethical layer. Following initial training, the RL model undergoes ethical fine-tuning, where human feedback…

计算机与社会 · 计算机科学 2026-05-05 Rohit K. Dubey , Damian Dailisan , Sachit Mahajan