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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…

Large language models (LLMs) are a promising venue for natural language understanding and generation. However, current LLMs are far from reliable: they are prone to generating non-factual information and, more crucially, to contradicting…

Computation and Language · Computer Science 2024-09-24 Diego Calanzone , Stefano Teso , Antonio Vergari

Large language models (LLMs) regularly demonstrate new and impressive performance on a wide range of language, knowledge, and reasoning benchmarks. Such rapid progress has led many commentators to argue that LLM general cognitive…

Computation and Language · Computer Science 2025-02-21 James Fodor

Large language models (LLMs) have achieved impressive results in natural language processing but are prone to memorizing portions of their training data, which can compromise evaluation metrics, raise privacy concerns, and limit…

Machine Learning · Computer Science 2024-12-03 Eduardo Slonski

Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely regarded as its core generative engine. Large language models (LLMs) have recently demonstrated…

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…

Computation and Language · Computer Science 2024-09-12 David Ilić , Gilles E. Gignac

Large language models (LLMs) have recently shown remarkable performance in language tasks and beyond. However, due to their limited inherent causal reasoning ability, LLMs still face challenges in handling tasks that require robust causal…

Computation and Language · Computer Science 2025-03-13 Xin Li , Zhuo Cai , Shoujin Wang , Kun Yu , Fang Chen

The rapid evolution of Large Language Models (LLMs) presents a promising solution to the global shortage of mental health professionals. However, their alignment with essential counseling competencies remains underexplored. We introduce…

Large Language Models have shown tremendous performance on a large variety of natural language processing tasks, ranging from text comprehension to common sense reasoning. However, the mechanisms responsible for this success remain opaque,…

Computation and Language · Computer Science 2024-01-04 Gaël Gendron , Qiming Bao , Michael Witbrock , Gillian Dobbie

Large Language Models (LLMs) excel in generating personalized content and facilitating interactive dialogues, showcasing their remarkable aptitude for a myriad of applications. However, their capabilities in reasoning and providing…

Computation and Language · Computer Science 2024-02-16 Min Zhang , Sato Takumi , Jack Zhang , Jun Wang

With the emergence of advanced reasoning models like OpenAI o3 and DeepSeek-R1, large language models (LLMs) have demonstrated remarkable reasoning capabilities. However, their ability to perform rigorous logical reasoning remains an open…

Artificial Intelligence · Computer Science 2025-02-14 Hanmeng Liu , Zhizhang Fu , Mengru Ding , Ruoxi Ning , Chaoli Zhang , Xiaozhang Liu , Yue Zhang

Recent studies suggest that the representations learned by large language models (LLMs) are partially aligned to those of the human brain. However, whether and why this alignment score arises from a similar sequence of computations remains…

Machine Learning · Computer Science 2025-12-02 Joséphine Raugel , Stéphane d'Ascoli , Jérémy Rapin , Valentin Wyart , Jean-Rémi King

Human decision-making belongs to the foundation of our society and civilization, but we are on the verge of a future where much of it will be delegated to artificial intelligence. The arrival of Large Language Models (LLMs) has transformed…

Artificial Intelligence · Computer Science 2025-06-23 Hao Li , Gengrui Zhang , Petter Holme , Shuyue Hu , Zhen Wang

Intelligent systems must maintain and manipulate task-relevant information online to adapt to dynamic environments and changing goals. This capacity, known as working memory, is fundamental to human reasoning and intelligence. Despite…

Machine Learning · Computer Science 2026-04-14 Hua-Dong Xiong , Li Ji-An , Jiaqi Huang , Robert C. Wilson , Kwonjoon Lee , Xue-Xin Wei

Qualitative Spatial Reasoning is a well explored area of Knowledge Representation and Reasoning and has multiple applications ranging from Geographical Information Systems to Robotics and Computer Vision. Recently, many claims have been…

Computation and Language · Computer Science 2024-12-02 Anthony G Cohn , Robert E Blackwell

Causal inference has shown potential in enhancing the predictive accuracy, fairness, robustness, and explainability of Natural Language Processing (NLP) models by capturing causal relationships among variables. The emergence of generative…

Computation and Language · Computer Science 2025-03-24 Xiaoyu Liu , Paiheng Xu , Junda Wu , Jiaxin Yuan , Yifan Yang , Yuhang Zhou , Fuxiao Liu , Tianrui Guan , Haoliang Wang , Tong Yu , Julian McAuley , Wei Ai , Furong Huang

Recent studies have shown that Large Language Models (LLMs) can achieve strong reasoning performance by incorporating functional symbolic representations that abstractly describe graph traversal algorithms and step-by-step reasoning in…

Artificial Intelligence · Computer Science 2026-05-28 Phuong Minh Nguyen , Tien Huu Dang , Naoya Inoue

Large Language Models (LLMs) are versatile, yet they often falter in tasks requiring deep and reliable reasoning due to issues like hallucinations, limiting their applicability in critical scenarios. This paper introduces a rigorously…

Computation and Language · Computer Science 2023-11-21 Saizhuo Wang , Zhihan Liu , Zhaoran Wang , Jian Guo

Language is far more than a communication tool. A wealth of information - including but not limited to the identities, psychological states, and social contexts of its users - can be gleaned through linguistic markers, and such insights are…

Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language processing (NLP). Large language models typically consist of…

Quantitative Methods · Quantitative Biology 2025-02-04 Jiajia Liu , Mengyuan Yang , Yankai Yu , Haixia Xu , Tiangang Wang , Kang Li , Xiaobo Zhou
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