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The recent advances in large language models (LLMs) have revolutionized industries such as finance, marketing, and customer service by enabling sophisticated natural language processing tasks. However, the broad adoption of LLMs brings…

计算机与社会 · 计算机科学 2025-02-19 Berk Yilmaz , Huthaifa I. Ashqar

Large language models (LLMs) are transforming research on machine learning while galvanizing public debates. Understanding not only when these models work well and succeed but also why they fail and misbehave is of great societal relevance.…

计算与语言 · 计算机科学 2024-10-16 Julian Coda-Forno , Kristin Witte , Akshay K. Jagadish , Marcel Binz , Zeynep Akata , Eric Schulz

While Large Language Models (LLMs) have become ubiquitous in many fields, understanding and mitigating LLM biases is an ongoing issue. This paper provides a novel method for evaluating the demographic biases of various generative AI models.…

计算与语言 · 计算机科学 2025-06-16 Jack H Fagan , Ruhaan Juyaal , Amy Yue-Ming Yu , Siya Pun

Gender bias in artificial intelligence (AI) and natural language processing has garnered significant attention due to its potential impact on societal perceptions and biases. This research paper aims to analyze gender bias in Large Language…

计算与语言 · 计算机科学 2023-09-04 Vishesh Thakur

Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A critical technique in leveraging their potential is role-playing, where LLMs simulate diverse roles…

计算机与社会 · 计算机科学 2026-04-23 Xinyue Li , Zhenpeng Chen , Jie M. Zhang , Ying Xiao , Tianlin Li , Weisong Sun , Yang Liu , Yiling Lou , Xuanzhe Liu

As language models (LMs) advance, interest is growing in applying them to high-stakes societal decisions, such as determining financing or housing eligibility. However, their potential for discrimination in such contexts raises ethical…

Recent advancements in Large Language Models (LLMs) have made them a popular information-seeking tool among end users. However, the statistical training methods for LLMs have raised concerns about their representation of under-represented…

Large Language Models (LLMs) have revolutionised the capability of AI models in comprehending and generating natural language text. They are increasingly being used to empower and deploy agents in real-world scenarios, which make decisions…

人工智能 · 计算机科学 2024-08-21 Sagar Uprety , Amit Kumar Jaiswal , Haiming Liu , Dawei Song

Large Language Models (LLMs) have made substantial progress in the past several months, shattering state-of-the-art benchmarks in many domains. This paper investigates LLMs' behavior with respect to gender stereotypes, a known issue for…

计算与语言 · 计算机科学 2023-08-30 Hadas Kotek , Rikker Dockum , David Q. Sun

Cognitive biases are systematic deviations in thinking that lead to irrational judgments and problematic decision-making, extensively studied across various fields. Recently, large language models (LLMs) have shown advanced understanding…

计算与语言 · 计算机科学 2024-10-10 Nuo Chen , Jiqun Liu , Xiaoyu Dong , Qijiong Liu , Tetsuya Sakai , Xiao-Ming Wu

Large Language Models (LLMs) have demonstrated remarkable capabilities in executing tasks based on natural language queries. However, these models, trained on curated datasets, inherently embody biases ranging from racial to national and…

计算与语言 · 计算机科学 2024-07-29 Lynnette Hui Xian Ng , Iain Cruickshank , Roy Ka-Wei Lee

The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, personalized, and interactive content generation at an unprecedented scale. In this paper, we…

计算与语言 · 计算机科学 2026-04-22 Sander Noels , Alexander Rogiers , Maarten Buyl , Tijl De Bie

Large language models (LLMs) can pass explicit social bias tests but still harbor implicit biases, similar to humans who endorse egalitarian beliefs yet exhibit subtle biases. Measuring such implicit biases can be a challenge: as LLMs…

计算机与社会 · 计算机科学 2024-05-24 Xuechunzi Bai , Angelina Wang , Ilia Sucholutsky , Thomas L. Griffiths

Large Language Models (LLMs) push the bound-aries in natural language processing and generative AI, driving progress across various aspects of modern society. Unfortunately, the pervasive issue of bias in LLMs responses (i.e., predictions)…

计算与语言 · 计算机科学 2025-05-20 Isabela Pereira Gregio , Ian Pons , Anna Helena Reali Costa , Artur Jordão

As Large language models (LLMs) become increasingly integrated into our lives, their inherent social biases remain a pressing concern. Detecting and evaluating these biases can be challenging because they are often implicit rather than…

计算与语言 · 计算机科学 2025-10-29 Katherine Abramski , Giulio Rossetti , Massimo Stella

Recent research has explored LLMs as scalable tools for relevance labeling, but studies indicate they are susceptible to priming effects, where prior relevance judgments influence later ones. Although psychological theories link personality…

计算与语言 · 计算机科学 2025-12-02 Nuo Chen , Hanpei Fang , Jiqun Liu , Wilson Wei , Tetsuya Sakai , Xiao-Ming Wu

Recommender systems are essential for delivering personalized content across digital platforms by modeling user preferences and behaviors. Recently, large language models (LLMs) have been adopted for prompt-based recommendation due to their…

信息检索 · 计算机科学 2025-05-28 Md Aminul Islam , Ahmed Sayeed Faruk

Large Language Models (LLMs) have revolutionized artificial intelligence, demonstrating remarkable computational power and linguistic capabilities. However, these models are inherently prone to various biases stemming from their training…

计算与语言 · 计算机科学 2025-02-14 Riccardo Cantini , Giada Cosenza , Alessio Orsino , Domenico Talia

Large language models (LLMs) increasingly operate in high-stakes settings including healthcare and medicine, where demographic attributes such as race and ethnicity may be explicitly stated or implicitly inferred from text. However,…

计算与语言 · 计算机科学 2026-01-21 Shiyue Hu , Ruizhe Li , Yanjun Gao

Large Language Models (LLMs) excel in Natural Language Processing (NLP) tasks, but they often propagate biases embedded in their training data, which is potentially impactful in sensitive domains like healthcare. While existing benchmarks…

计算与语言 · 计算机科学 2026-03-11 Trung Hieu Ngo , Adrien Bazoge , Solen Quiniou , Pierre-Antoine Gourraud , Emmanuel Morin