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The rise of Large Language Models (LLMs) like ChatGPT has advanced natural language processing, yet concerns about cognitive biases are growing. In this paper, we investigate the anchoring effect, a cognitive bias where the mind relies…

计算与语言 · 计算机科学 2026-03-31 Yiming Huang , Biquan Bie , Zuqiu Na , Weilin Ruan , Songxin Lei , Yutao Yue , Xinlei He

The advent of Large Language Models (LLMs) has revolutionized product recommenders, yet their susceptibility to adversarial manipulation poses critical challenges, particularly in real-world commercial applications. Our approach is the…

计算与语言 · 计算机科学 2025-10-23 Giorgos Filandrianos , Angeliki Dimitriou , Maria Lymperaiou , Konstantinos Thomas , Giorgos Stamou

This paper investigates the influence of cognitive biases on Large Language Models (LLMs) outputs. Cognitive biases, such as confirmation and availability biases, can distort user inputs through prompts, potentially leading to unfaithful…

计算与语言 · 计算机科学 2025-06-17 Yan Sun , Stanley Kok

Large Language Models (LLMs) are increasingly used in decision-making, yet their susceptibility to cognitive biases remains a pressing challenge. This study explores how personality traits influence these biases and evaluates the…

人工智能 · 计算机科学 2025-02-21 Jiangen He , Jiqun Liu

Large language models (LLMs) are increasingly examined as both behavioral subjects and decision systems, yet it remains unclear whether observed cognitive biases reflect surface imitation or deeper probability shifts. Anchoring bias, a…

人工智能 · 计算机科学 2025-11-11 Felipe Valencia-Clavijo

Large Language Models (LLMs) like GPT-4 and Gemini have significantly advanced artificial intelligence by enabling machines to generate and comprehend human-like text. Despite their impressive capabilities, LLMs are not immune to…

计算与语言 · 计算机科学 2024-12-19 Jiaxu Lou , Yifan Sun

Large Language Models (LLMs) such as ChatGPT have received enormous attention over the past year and are now used by hundreds of millions of people every day. The rapid adoption of this technology naturally raises questions about the…

人工智能 · 计算机科学 2024-03-15 Jonathan Shaki , Sarit Kraus , Michael Wooldridge

Do generative AI models, particularly large language models (LLMs), exhibit systematic behavioral biases in economic and financial decisions? If so, how can these biases be mitigated? Drawing on the cognitive psychology and experimental…

综合经济学 · 经济学 2026-02-11 Pietro Bini , Lin William Cong , Xing Huang , Lawrence J. Jin

Large Language Models (LLMs) are trained on large corpora written by humans and demonstrate high performance on various tasks. However, as humans are susceptible to cognitive biases, which can result in irrational judgments, LLMs can also…

计算与语言 · 计算机科学 2024-12-03 Yasuaki Sumita , Koh Takeuchi , Hisashi Kashima

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

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) are increasingly deployed in socially sensitive settings despite substantial documentation that they encode gender biases. Chain-of-Thought (CoT) prompting has been proposed as a bias-mitigation approach.…

计算与语言 · 计算机科学 2026-05-21 Edie Pearman , Sophia Osborne , Mira Kandlikar-Bloch , Mina Arzaghi , Florian Carichon , Golnoosh Farnadi

While Large Language Models (LLMs) demonstrate impressive reasoning capabilities, growing evidence suggests much of their success stems from memorized answer-reasoning patterns rather than genuine inference. In this work, we investigate a…

计算与语言 · 计算机科学 2025-06-24 Yang Wu , Yifan Zhang , Yiwei Wang , Yujun Cai , Yurong Wu , Yuran Wang , Ning Xu , Jian Cheng

Large Language Models (LLMs) are transforming human decision-making by acting as cognitive collaborators. Yet, this promise comes with a paradox: while LLMs can improve accuracy, they may also erode independent reasoning, promote…

密码学与安全 · 计算机科学 2025-09-09 Irdin Pekaric , Philipp Zech , Tom Mattson

Financial markets are influenced by human behavior that deviates from rationality due to cognitive biases. Traditional reinforcement learning (RL) models for financial decision-making assume rational agents, potentially overlooking the…

机器学习 · 计算机科学 2026-01-14 Liu He

Cognitive biases often shape human decisions. While large language models (LLMs) have been shown to reproduce well-known biases, a more critical question is whether LLMs can predict biases at the individual level and emulate the dynamics of…

人工智能 · 计算机科学 2026-02-27 Stephen Pilli , Vivek Nallur

Large language models (LLMs) offer significant potential as tools to support an expanding range of decision-making tasks. Given their training on human (created) data, LLMs have been shown to inherit societal biases against protected…

人工智能 · 计算机科学 2024-10-07 Jessica Echterhoff , Yao Liu , Abeer Alessa , Julian McAuley , Zexue He

Large language models (LLMs) have the potential to aid and improve human decision-making in classification tasks, not only by providing fairly accurate predictions, but also in their ability to generate cogent narrative explanations of…

人机交互 · 计算机科学 2026-05-25 Laura R. Marusich , Mary Grace Kozuch Dhooghe , Jonathan Z. Bakdash , Murat Kantarcioglu

As modern large language models (LLMs) become integral to everyday tasks, concerns about their inherent biases and their potential impact on human decision-making have emerged. While bias in models are well-documented, less is known about…

Do large language models (LLMs) display rational reasoning? LLMs have been shown to contain human biases due to the data they have been trained on; whether this is reflected in rational reasoning remains less clear. In this paper, we answer…

计算与语言 · 计算机科学 2024-02-16 Olivia Macmillan-Scott , Mirco Musolesi
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