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The capabilities of large language models (LLMs) have raised concerns about their potential to create and propagate convincing narratives. Here, we study their performance in detecting convincing arguments to gain insights into LLMs'…

计算与语言 · 计算机科学 2024-10-07 Paula Rescala , Manoel Horta Ribeiro , Tiancheng Hu , Robert West

This study investigates whether large language models (LLMs) mirror human neurocognition during abstract reasoning. We compared the performance and neural representations of human participants with those of eight open-source LLMs on an…

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

计算与语言 · 计算机科学 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

Large Language Models (LLMs) have reshaped our world with significant advancements in science, engineering, and society through applications ranging from scientific discoveries and medical diagnostics to Chatbots. Despite their ubiquity and…

人工智能 · 计算机科学 2025-08-26 Kushal Raj Bhandari , Pin-Yu Chen , Jianxi Gao

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

计算与语言 · 计算机科学 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Large Language Models (LLMs) excel in handling general knowledge tasks, yet they struggle with user-specific personalization, such as understanding individual emotions, writing styles, and preferences. Personalized Large Language Models…

人工智能 · 计算机科学 2025-09-23 Jiahong Liu , Zexuan Qiu , Zhongyang Li , Quanyu Dai , Wenhao Yu , Jieming Zhu , Minda Hu , Menglin Yang , Tat-Seng Chua , Irwin King

We investigate whether Large Language Models (LLMs) exhibit human-like cognitive patterns under four established frameworks from psychology: Thematic Apperception Test (TAT), Framing Bias, Moral Foundations Theory (MFT), and Cognitive…

人工智能 · 计算机科学 2025-12-12 Akash Kundu , Rishika Goswami

The zero-shot capability of Large Language Models (LLMs) has enabled highly flexible, reference-free metrics for various tasks, making LLM evaluators common tools in NLP. However, the robustness of these LLM evaluators remains relatively…

计算与语言 · 计算机科学 2024-05-06 Rickard Stureborg , Dimitris Alikaniotis , Yoshi Suhara

Large Language Models (LLMs) stand at the forefront of a number of Natural Language Processing (NLP) tasks. Despite the widespread adoption of LLMs in NLP, much of their potential in broader fields remains largely unexplored, and…

机器学习 · 计算机科学 2024-03-11 Zhiqiang Zhong , Kuangyu Zhou , Davide Mottin

Large Language Models (LLMs) are capable of displaying a wide range of abilities that are not directly connected with the task for which they are trained: predicting the next words of human-written texts. In this article, I review recent…

人工智能 · 计算机科学 2023-12-19 Stefano Nolfi

In the field of Artificial (General) Intelligence (AI), the several recent advancements in Natural language processing (NLP) activities relying on Large Language Models (LLMs) have come to encourage the adoption of LLMs as scientific models…

计算与语言 · 计算机科学 2023-10-18 Evelina Leivada , Vittoria Dentella , Elliot Murphy

Understanding how humans conceptualize and categorize natural objects offers critical insights into perception and cognition. With the advent of Large Language Models (LLMs), a key question arises: can these models develop human-like object…

Given the remarkable capabilities of large language models (LLMs), there has been a growing interest in evaluating their similarity to the human brain. One approach towards quantifying this similarity is by measuring how well a model…

计算与语言 · 计算机科学 2024-06-24 Ebrahim Feghhi , Nima Hadidi , Bryan Song , Idan A. Blank , Jonathan C. Kao

Analogical reasoning -- the capacity to identify and map structural relationships between different domains -- is fundamental to human cognition and learning. Recent studies have shown that large language models (LLMs) can sometimes match…

计算与语言 · 计算机科学 2025-11-21 Sam Musker , Alex Duchnowski , Raphaël Millière , Ellie Pavlick

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs,…

计算与语言 · 计算机科学 2023-10-10 Thilo Hagendorff , Sarah Fabi

Metacognition--the capacity to monitor and evaluate one's own knowledge and performance--is foundational to human decision-making, learning, and communication. As large language models (LLMs) become increasingly embedded in both high-stakes…

人工智能 · 计算机科学 2025-10-14 Mark Steyvers , Megan A. K. Peters

Deductive reasoning plays a pivotal role in the formulation of sound and cohesive arguments. It allows individuals to draw conclusions that logically follow, given the truth value of the information provided. Recent progress in the domain…

计算与语言 · 计算机科学 2024-06-04 Philipp Mondorf , Barbara Plank

This paper presents a comprehensive evaluation of the capabilities of Large Language Models (LLMs) in metaphor interpretation across multiple datasets, tasks, and prompt configurations. Although metaphor processing has gained significant…

计算与语言 · 计算机科学 2025-07-22 Elisa Sanchez-Bayona , Rodrigo Agerri

Large language models (LLMs) are advanced artificial intelligence (AI) systems that can perform a variety of tasks commonly found in human intelligence tests, such as defining words, performing calculations, and engaging in verbal…

计算与语言 · 计算机科学 2024-09-12 David Ilić , Gilles E. Gignac

With the increasing interest in using large language models (LLMs) for planning in natural language, understanding their behaviors becomes an important research question. This work conducts a systematic investigation of LLMs' ability to…

计算与语言 · 计算机科学 2025-02-18 Yixuan Wang , Freda Shi