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Large Language Models (LLMs) excel at providing information acquired during pretraining on large-scale corpora and following instructions through user prompts. This study investigates whether the quality of LLM responses varies depending on…

计算与语言 · 计算机科学 2025-11-19 Manon Reusens , Philipp Borchert , Jochen De Weerdt , Bart Baesens

Large language models (LLMs) are increasingly being used in user-facing applications, from providing medical consultations to job interview advice. Recent research suggests that these models are becoming increasingly proficient at inferring…

计算与语言 · 计算机科学 2025-07-22 Matthew Kearney , Reuben Binns , Yarin Gal

Factuality is a necessary precursor to useful educational tools. As adoption of Large Language Models (LLMs) in education continues of grow, ensuring correctness in all settings is paramount. Despite their strong English capabilities, LLM…

计算与语言 · 计算机科学 2025-06-09 Yuval Kansal , Shmuel Berman , Lydia Liu

The conformity effect describes the tendency of individuals to align their responses with the majority. Studying this bias in large language models (LLMs) is crucial, as LLMs are increasingly used in various information-seeking and…

计算与语言 · 计算机科学 2025-05-27 Xiaochen Zhu , Caiqi Zhang , Tom Stafford , Nigel Collier , Andreas Vlachos

Large language models (LLM) are generating information at a rapid pace, requiring users to increasingly rely and trust the data. Despite remarkable advances of LLM, Information generated by LLM is not completely trustworthy, due to…

计算与语言 · 计算机科学 2024-01-25 Rick Rejeleene , Xiaowei Xu , John Talburt

Instruction-tuning enhances the ability of large language models (LLMs) to follow user instructions more accurately, improving usability while reducing harmful outputs. However, this process may increase the model's dependence on user…

计算与语言 · 计算机科学 2025-07-25 Kyubeen Han , Junseo Jang , Hongjin Kim , Geunyeong Jeong , Harksoo Kim

Large Language Models (LLMs) have been evaluated using diverse question types, e.g., multiple-choice, true/false, and short/long answers. This study answers an unexplored question about the impact of different question types on LLM accuracy…

计算与语言 · 计算机科学 2026-04-29 Seok Hwan Song , Mohna Chakraborty , Qi Li , Wallapak Tavanapong

In the age of misinformation, hallucination - the tendency of Large Language Models (LLMs) to generate non-factual or unfaithful responses - represents the main risk for their global utility. Despite LLMs becoming increasingly multilingual,…

计算与语言 · 计算机科学 2026-02-03 Saad Obaid ul Islam , Anne Lauscher , Goran Glavaš

Large language models (LLMs) are increasingly being adopted in educational settings. These applications expand beyond English, though current LLMs remain primarily English-centric. In this work, we ascertain if their use in education…

计算与语言 · 计算机科学 2025-08-06 Vansh Gupta , Sankalan Pal Chowdhury , Vilém Zouhar , Donya Rooein , Mrinmaya Sachan

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

Large language models (LLMs) can produce erroneous responses that sound fluent and convincing, raising the risk that users will rely on these responses as if they were correct. Mitigating such overreliance is a key challenge. Through a…

人机交互 · 计算机科学 2025-02-13 Sunnie S. Y. Kim , Jennifer Wortman Vaughan , Q. Vera Liao , Tania Lombrozo , Olga Russakovsky

What makes an interaction with the LLM more preferable for the user? While it is intuitive to assume that information accuracy in the LLM's responses would be one of the influential variables, recent studies have found that inaccurate LLM's…

计算与语言 · 计算机科学 2025-04-25 Rendi Chevi , Kentaro Inui , Thamar Solorio , Alham Fikri Aji

Large Language Models (LLMs) play a critical role in how humans access information. While their core use relies on comprehending written requests, our understanding of this ability is currently limited, because most benchmarks evaluate LLMs…

The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds that language models can use tools in ways that contradict the interests or explicit instructions…

机器学习 · 计算机科学 2026-04-24 Kushal Agrawal , Frank Xiao , Guido Bergman , Asa Cooper Stickland

Large Language Models (LLMs) have demonstrated exceptional natural language understanding abilities and have excelled in a variety of natural language processing (NLP)tasks in recent years. Despite the fact that most LLMs are trained…

计算与语言 · 计算机科学 2023-10-25 Xiang Zhang , Senyu Li , Bradley Hauer , Ning Shi , Grzegorz Kondrak

Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reproduce patterns of susceptibility to misinformation remains unclear. We test whether LLM-simulated…

社会与信息网络 · 计算机科学 2026-04-13 Eun Cheol Choi , Lindsay E. Young , Emilio Ferrara

Large language models (LLMs) have demonstrated impressive capabilities across a variety of tasks, but their increasing autonomy in real-world applications raises concerns about their trustworthiness. While hallucinations-unintentional…

机器学习 · 计算机科学 2025-09-04 Haoran Huan , Mihir Prabhudesai , Mengning Wu , Shantanu Jaiswal , Deepak Pathak

The development of highly fluent large language models (LLMs) has prompted increased interest in assessing their reasoning and problem-solving capabilities. We investigate whether several LLMs can solve a classic type of deductive reasoning…

计算与语言 · 计算机科学 2024-04-16 Spencer M. Seals , Valerie L. Shalin

As Large Language Models (LLMs) become widely used to model and simulate human behavior, understanding their biases becomes critical. We developed an experimental framework using Big Five personality surveys and uncovered a previously…

Large Language Models (LLMs) are able to provide assistance on a wide range of information-seeking tasks. However, model outputs may be misleading, whether unintentionally or in cases of intentional deception. We investigate the ability of…

计算与语言 · 计算机科学 2024-07-17 Betty Li Hou , Kejian Shi , Jason Phang , James Aung , Steven Adler , Rosie Campbell
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