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In this paper, we explore the capabilities of state-of-the-art large language models (LLMs) such as GPT-4, GPT-4o, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro, Llama 3, and Llama 3.1 in solving some selected undergraduate-level…

人工智能 · 计算机科学 2024-08-16 Usman Syed , Ethan Light , Xingang Guo , Huan Zhang , Lianhui Qin , Yanfeng Ouyang , Bin Hu

The assessment of bias within Large Language Models (LLMs) has emerged as a critical concern in the contemporary discourse surrounding Artificial Intelligence (AI) in the context of their potential impact on societal dynamics. Recognizing…

计算与语言 · 计算机科学 2024-06-06 Luca Rettenberger , Markus Reischl , Mark Schutera

Large Language Models (LLMs) exhibit surprisingly diverse risk preferences when acting as AI decision makers, a crucial characteristic whose origins remain poorly understood despite their expanding economic roles. We analyze 50 LLMs using…

综合经济学 · 经济学 2025-06-11 Shumiao Ouyang , Hayong Yun , Xingjian Zheng

Political biases in Large Language Model (LLM)-based artificial intelligence (AI) systems, such as OpenAI's ChatGPT or Google's Gemini, have been previously reported. While several prior studies have attempted to quantify these biases using…

计算机与社会 · 计算机科学 2025-03-17 David Rozado

The purpose of this study is to assess how large language models (LLMs) can be used for fact-checking and contribute to the broader debate on the use of automated means for veracity identification. To achieve this purpose, we use AI…

The advancement of large language models (LLMs) has demonstrated strong capabilities across various applications, including mental health analysis. However, existing studies have focused on predictive performance, leaving the critical issue…

Large Language Models (LLMs) have revolutionized both general natural language processing and domain-specific applications such as code synthesis, legal reasoning, and finance. However, while prior studies have explored individual model…

软件工程 · 计算机科学 2025-12-05 Gunjan Das , Paheli Bhattacharya , Rishabh Gupta

Political bias in Large Language Models (LLMs) presents a growing concern for the responsible deployment of AI systems. Traditional audits often attempt to locate a model's political position as a point estimate, masking the broader set of…

计算机与社会 · 计算机科学 2025-09-12 Leif Azzopardi , Yashar Moshfeghi

Employers increasingly expect graduates to utilize large language models (LLMs) in the workplace, yet the competencies needed for computing roles across Africa remain unclear given varying national contexts. This study examined how six…

计算机与社会 · 计算机科学 2026-02-02 Precious Eze , Stephanie Lunn , Bruk Berhane

As large language models (LLMs) are increasingly deployed, understanding how they express political positioning is important for evaluating alignment and downstream effects. We audit 26 contemporary LLMs using three political psychometric…

计算机与社会 · 计算机科学 2026-03-18 Adib Sakhawat , Tahsin Islam , Takia Farhin , Syed Rifat Raiyan , Hasan Mahmud , Md Kamrul Hasan

Large Language Models (LLMs) have emerged as powerful candidates to inform clinical decision-making processes. While these models play an increasingly prominent role in shaping the digital landscape, two growing concerns emerge in…

计算与语言 · 计算机科学 2024-04-24 Raphael Poulain , Hamed Fayyaz , Rahmatollah Beheshti

Large Language Models (LLMs) achieve strong performance on diverse tasks but often exhibit cognitive inertia, struggling to follow instructions that conflict with the standardized patterns learned during supervised fine-tuning (SFT). To…

This study presents a comprehensive comparative evaluation of four state-of-the-art Large Language Models (LLMs)--Claude 3.7 Sonnet, DeepSeek-V3, Gemini 2.0 Flash, and GPT-4o--for sentiment analysis and emotion detection in Persian social…

计算与语言 · 计算机科学 2025-09-19 Kian Tohidi , Kia Dashtipour , Simone Rebora , Sevda Pourfaramarz

Large language models (LLMs) are increasingly deployed in politically sensitive settings, raising concerns about their potential to encode, amplify, or be steered toward specific ideologies. We investigate how adopting synthetic personas…

计算与语言 · 计算机科学 2025-08-25 Pietro Bernardelle , Stefano Civelli , Leon Fröhling , Riccardo Lunardi , Kevin Roitero , Gianluca Demartini

As AI systems become more integrated into daily life, the need for safer and more reliable moderation has never been greater. Large Language Models (LLMs) have demonstrated remarkable capabilities, surpassing earlier models in complexity…

人工智能 · 计算机科学 2026-01-13 Naseem Machlovi , Maryam Saleki , Innocent Ababio , Ruhul Amin

Large Language Models (LLMs) have an increasing impact on our lives with use cases such as chatbots, study support, coding support, ideation, writing assistance, and more. Previous studies have revealed linguistic biases in pronouns used to…

计算与语言 · 计算机科学 2024-06-17 Smilla Due , Sneha Das , Marianne Andersen , Berta Plandolit López , Sniff Andersen Nexø , Line Clemmensen

The Large Language Model Bias Index (LLMBI) is a pioneering approach designed to quantify and address biases inherent in large language models (LLMs), such as GPT-4. We recognise the increasing prevalence and impact of LLMs across diverse…

计算与语言 · 计算机科学 2024-01-01 Abiodun Finbarrs Oketunji , Muhammad Anas , Deepthi Saina

Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These models have become popular in artificial intelligence (AI)…

Preference optimization techniques have become a standard final stage for training state-of-art large language models (LLMs). However, despite widespread adoption, the vast majority of work to-date has focused on first-class citizen…

计算与语言 · 计算机科学 2024-07-04 John Dang , Arash Ahmadian , Kelly Marchisio , Julia Kreutzer , Ahmet Üstün , Sara Hooker

This study introduces a framework for evaluating consistency in large language model (LLM) binary text classification, addressing the lack of established reliability assessment methods. Adapting psychometric principles, we determine sample…