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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…

计算与语言 · 计算机科学 2024-02-16 Min Zhang , Sato Takumi , Jack Zhang , Jun Wang

Logical reasoning consistently plays a fundamental and significant role in the domains of knowledge engineering and artificial intelligence. Recently, Large Language Models (LLMs) have emerged as a noteworthy innovation in natural language…

计算与语言 · 计算机科学 2024-09-17 Fangzhi Xu , Qika Lin , Jiawei Han , Tianzhe Zhao , Jun Liu , Erik Cambria

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

The performance of Large language models (LLMs) across a broad range of domains has been impressive but have been critiqued as not being able to reason about their process and conclusions derived. This is to explain the conclusions draw,…

计算与语言 · 计算机科学 2024-10-30 Rob Sullivan , Nelly Elsayed

Large language models (LLM) have revolutionized the processing of natural language. Although first benchmarks of the process modeling abilities of LLM are promising, it is currently under debate to what extent an LLM can generate good…

计算与语言 · 计算机科学 2025-03-19 Peter Fettke , Constantin Houy

Current Large Language Models (LLMs) are unparalleled in their ability to generate grammatically correct, fluent text. LLMs are appearing rapidly, and debates on LLM capacities have taken off, but reflection is lagging behind. Thus, in this…

计算与语言 · 计算机科学 2023-11-01 Bram M. A. van Dijk , Tom Kouwenhoven , Marco R. Spruit , Max J. van Duijn

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

人工智能 · 计算机科学 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress in…

计算与语言 · 计算机科学 2023-05-29 Jie Huang , Kevin Chen-Chuan Chang

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

机器学习 · 计算机科学 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique

Due to the remarkable language understanding and generation abilities of large language models (LLMs), their use in educational applications has been explored. However, little work has been done on investigating the pedagogical ability of…

计算与语言 · 计算机科学 2023-10-23 An-Zi Yen , Wei-Ling Hsu

Large language models (LLMs) demonstrate extraordinary abilities in a wide range of natural language processing (NLP) tasks. In this paper, we show that, beyond text understanding capability, LLMs are capable of processing text layouts that…

计算与语言 · 计算机科学 2024-08-29 Weiming Li , Manni Duan , Dong An , Yan Shao

Advances in the general capabilities of large language models (LLMs) have led to their use for information retrieval, and as components in automated decision systems. A faithful representation of probabilistic reasoning in these models may…

人工智能 · 计算机科学 2025-04-21 Gabriel Freedman , Francesca Toni

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

Large language models (LLMs) show remarkable capabilities across a variety of tasks. Despite the models only seeing text in training, several recent studies suggest that LLM representations implicitly capture aspects of the underlying…

计算与语言 · 计算机科学 2024-04-16 Yutaro Yamada , Yihan Bao , Andrew K. Lampinen , Jungo Kasai , Ilker Yildirim

We assess the ability of large language models (LLMs) to answer causal questions by analyzing their strengths and weaknesses against three types of causal question. We believe that current LLMs can answer causal questions with existing…

Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as superior in handling various natural language processing tasks…

计算与语言 · 计算机科学 2023-11-30 Han Cao , Lingwei Wei , Mengyang Chen , Wei Zhou , Songlin Hu

Interpretable machine learning has exploded as an area of interest over the last decade, sparked by the rise of increasingly large datasets and deep neural networks. Simultaneously, large language models (LLMs) have demonstrated remarkable…

计算与语言 · 计算机科学 2024-02-06 Chandan Singh , Jeevana Priya Inala , Michel Galley , Rich Caruana , Jianfeng Gao

We investigate whether large language models (LLMs) can predict whether they will succeed on a given task and whether their predictions improve as they progress through multi-step tasks. We also investigate whether LLMs can learn from…

计算与语言 · 计算机科学 2026-01-01 Casey O. Barkan , Sid Black , Oliver Sourbut

Large language models (LLMs) have achieved remarkable performance in language understanding and generation tasks by leveraging vast amounts of online texts. Unlike conventional models, LLMs can adapt to new domains through prompt…

人工智能 · 计算机科学 2024-06-18 Ming Cheung

Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of research contributions in this direction. These works…

计算与语言 · 计算机科学 2024-10-18 Humza Naveed , Asad Ullah Khan , Shi Qiu , Muhammad Saqib , Saeed Anwar , Muhammad Usman , Naveed Akhtar , Nick Barnes , Ajmal Mian
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