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Recent generations of language models have introduced Large Reasoning Models (LRMs) that generate detailed thinking processes before providing answers. While these models demonstrate improved performance on reasoning benchmarks, their…

Artificial Intelligence · Computer Science 2025-11-21 Parshin Shojaee , Iman Mirzadeh , Keivan Alizadeh , Maxwell Horton , Samy Bengio , Mehrdad Farajtabar

Large language models (LLMs) such as ChatGPT o1, ChatGPT o3, and DeepSeek R1 have shown great potential in solving difficult problems. However, current LLM evaluation benchmarks are limited to one-step interactions. Some of the existing…

Machine Learning · Computer Science 2025-12-01 Huanyu Li , Zongyuan Li , Wei Huang , Xian Guo

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

Large Language Models (LLMs) have recently achieved impressive performance in math and reasoning benchmarks. However, they often struggle with logic problems and puzzles that are relatively easy for humans. To further investigate this, we…

Artificial Intelligence · Computer Science 2025-09-16 Nasim Borazjanizadeh , Roei Herzig , Trevor Darrell , Rogerio Feris , Leonid Karlinsky

Evaluating reasoning ability in Large Language Models (LLMs) is important for advancing artificial intelligence, as it transcends mere linguistic task performance. It involves understanding whether these models truly understand information,…

Artificial Intelligence · Computer Science 2025-10-29 Benjamin Grando Moreira

This paper investigates the potential of AI models, particularly large language models (LLMs), to support knowledge exploration and augment human creativity during ideation. We present "Latent Lab" an interactive tool for discovering…

Artificial Intelligence · Computer Science 2023-11-23 Kevin Dunnell , Trudy Painter , Andrew Stoddard , Andy Lippman

Despite widespread success in language understanding and generation, large language models (LLMs) exhibit unclear and often inconsistent behavior when faced with tasks that require probabilistic reasoning. In this work, we present the first…

Computation and Language · Computer Science 2025-09-29 Mobina Pournemat , Keivan Rezaei , Gaurang Sriramanan , Arman Zarei , Jiaxiang Fu , Yang Wang , Hamid Eghbalzadeh , Soheil Feizi

Recent advancements in natural language processing by large language models (LLMs), such as GPT-4, have been suggested to approach Artificial General Intelligence. And yet, it is still under dispute whether LLMs possess similar reasoning…

Computation and Language · Computer Science 2024-02-02 Eugenio Herrera-Berg , Tomás Vergara Browne , Pablo León-Villagrá , Marc-Lluís Vives , Cristian Buc Calderon

Recently developed large language models (LLMs) have been shown to perform remarkably well on a wide range of language understanding tasks. But, can they really "reason" over the natural language? This question has been receiving…

Computation and Language · Computer Science 2024-06-07 Mihir Parmar , Nisarg Patel , Neeraj Varshney , Mutsumi Nakamura , Man Luo , Santosh Mashetty , Arindam Mitra , Chitta Baral

As large language models (LLMs) have demonstrated strong reasoning abilities in structured tasks (e.g., coding and mathematics), we explore whether these abilities extend to strategic multi-agent environments. We investigate strategic…

General Economics · Economics 2025-10-23 Gavin Kader , Dongwoo Lee

Language has long been conceived as an essential tool for human reasoning. The breakthrough of Large Language Models (LLMs) has sparked significant research interest in leveraging these models to tackle complex reasoning tasks. Researchers…

Large Language Models (LLMs) exhibit impressive reasoning abilities, yet their reliance on structured step-by-step processing reveals a critical limitation. In contrast, human cognition fluidly adapts between intuitive, heuristic (System 1)…

Computation and Language · Computer Science 2025-10-16 Alireza S. Ziabari , Nona Ghazizadeh , Zhivar Sourati , Farzan Karimi-Malekabadi , Payam Piray , Morteza Dehghani

Exploring the capabilities of Large Language Models (LLMs) in puzzle solving unveils critical insights into their potential and challenges in AI, marking a significant step towards understanding their applicability in complex reasoning…

Computation and Language · Computer Science 2025-08-04 Panagiotis Giadikiaroglou , Maria Lymperaiou , Giorgos Filandrianos , Giorgos Stamou

Recent advancements in Large Reasoning Models (LRMs), such as OpenAI's o1/o3 and DeepSeek-R1, have demonstrated remarkable performance in specialized reasoning tasks through human-like deliberative thinking and long chain-of-thought…

Artificial Intelligence · Computer Science 2025-11-20 Weixiang Zhao , Xingyu Sui , Jiahe Guo , Yulin Hu , Yang Deng , Yanyan Zhao , Xuda Zhi , Yongbo Huang , Hao He , Wanxiang Che , Ting Liu , Bing Qin

Large Language Models (LLMs) have been touted as AI models possessing advanced reasoning abilities. However, recent works have shown that LLMs often bypass true reasoning using shortcuts, sparking skepticism. To study the reasoning…

Artificial Intelligence · Computer Science 2024-10-24 Rishi Hazra , Gabriele Venturato , Pedro Zuidberg Dos Martires , Luc De Raedt

Large language models (LLMs) can perform reasoning computations both internally within their latent space and externally by generating explicit token sequences like chains of thought. Significant progress in enhancing reasoning abilities…

Computation and Language · Computer Science 2025-04-16 Thilo Hagendorff , Sarah Fabi

Large Language Models (LLMs) have demonstrated remarkable progress in reasoning across diverse domains. However, effective reasoning in real-world tasks requires adapting the reasoning strategy to the demands of the problem, ranging from…

Computation and Language · Computer Science 2025-08-19 Xinda Jia , Jinpeng Li , Zezhong Wang , Jingjing Li , Xingshan Zeng , Yasheng Wang , Weinan Zhang , Yong Yu , Weiwen Liu

Recent advancements in Large Language Models (LLMs) have brought them closer to matching human cognition across a variety of tasks. How well do these models align with human performance in detecting and mapping analogies? Prior research has…

Computation and Language · Computer Science 2025-07-16 Kalit Inani , Keshav Kabra , Vijay Marupudi , Sashank Varma

Research into the external behaviors and internal mechanisms of large language models (LLMs) has shown promise in addressing complex tasks in the physical world. Studies suggest that powerful LLMs, like GPT-4, are beginning to exhibit…

Artificial Intelligence · Computer Science 2024-10-25 Miao Yu , Junyuan Mao , Guibin Zhang , Jingheng Ye , Junfeng Fang , Aoxiao Zhong , Yang Liu , Yuxuan Liang , Kun Wang , Qingsong Wen

Large language models (LLMs) have rapidly evolved from text generators into powerful problem solvers. Yet, many open tasks demand critical thinking, multi-source, and verifiable outputs, which are beyond single-shot prompting or standard…