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The potential of large language models (LLMs) to reason like humans has been a highly contested topic in Machine Learning communities. However, the reasoning abilities of humans are multifaceted and can be seen in various forms, including…

Computation and Language · Computer Science 2023-03-28 Shrivats Agrawal

Analogical reasoning is at the core of human cognition, serving as an important foundation for a variety of intellectual activities. While prior work has shown that LLMs can represent task patterns and surface-level concepts, it remains…

Computation and Language · Computer Science 2025-11-26 Taewhoo Lee , Minju Song , Chanwoong Yoon , Jungwoo Park , Jaewoo Kang

While large language models (LLMs) have demonstrated impressive capabilities across various natural language processing tasks by acquiring rich factual knowledge from their broad training data, their ability to synthesize and logically…

Computation and Language · Computer Science 2024-07-31 Tianshi Zheng , Jiaxin Bai , Yicheng Wang , Tianqing Fang , Yue Guo , Yauwai Yim , Yangqiu Song

Large Language Models (LLMs) are revolutionizing several areas of Artificial Intelligence. One of the most remarkable applications is creative writing, e.g., poetry or storytelling: the generated outputs are often of astonishing quality.…

Artificial Intelligence · Computer Science 2025-02-14 Giorgio Franceschelli , Mirco Musolesi

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

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

In the field of natural language processing, the rapid development of large language model (LLM) has attracted more and more attention. LLMs have shown a high level of creativity in various tasks, but the methods for assessing such…

Computation and Language · Computer Science 2025-02-21 Yunpu Zhao , Rui Zhang , Wenyi Li , Di Huang , Jiaming Guo , Shaohui Peng , Yifan Hao , Yuanbo Wen , Xing Hu , Zidong Du , Qi Guo , Ling Li , Yunji Chen

Artificial intelligence has, so far, largely automated routine tasks, but what does it mean for the future of work if Large Language Models (LLMs) show creativity comparable to humans? To measure the creativity of LLMs holistically, the…

Artificial Intelligence · Computer Science 2025-05-22 Luning Sun , Yuzhuo Yuan , Yuan Yao , Yanyan Li , Hao Zhang , Xing Xie , Xiting Wang , Fang Luo , David Stillwell

Hallucinations in large language models (LLMs) are always seen as limitations. However, could they also be a source of creativity? This survey explores this possibility, suggesting that hallucinations may contribute to LLM application by…

Artificial Intelligence · Computer Science 2024-02-13 Xuhui Jiang , Yuxing Tian , Fengrui Hua , Chengjin Xu , Yuanzhuo Wang , Jian Guo

Large language models are transforming the creative process by offering unprecedented capabilities to algorithmically generate ideas. While these tools can enhance human creativity when people co-create with them, it's unclear how this will…

Human-Computer Interaction · Computer Science 2025-02-18 Harsh Kumar , Jonathan Vincentius , Ewan Jordan , Ashton Anderson

In modern dialogue systems, the use of Large Language Models (LLMs) has grown exponentially due to their capacity to generate diverse, relevant, and creative responses. Despite their strengths, striking a balance between the LLMs'…

Computation and Language · Computer Science 2023-08-01 Chen Zhang

A hallmark of intelligence is the ability to use a familiar domain to make inferences about a less familiar domain, known as analogical reasoning. In this article, we delve into the performance of Large Language Models (LLMs) in dealing…

Artificial Intelligence · Computer Science 2023-09-13 Thilini Wijesiriwardene , Amit Sheth , Valerie L. Shalin , Amitava Das

Cross-domain alignment refers to the task of mapping a concept from one domain to another. For example, ``If a \textit{doctor} were a \textit{color}, what color would it be?''. This seemingly peculiar task is designed to investigate how…

Computation and Language · Computer Science 2024-05-24 Asaf Yehudai , Taelin Karidi , Gabriel Stanovsky , Ariel Goldstein , Omri Abend

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…

Computation and Language · Computer Science 2023-05-29 Jie Huang , Kevin Chen-Chuan Chang

Large Language Models (LLMs) are becoming vital tools that help us solve and understand complex problems by acting as digital assistants. LLMs can generate convincing explanations, even when only given the inputs and outputs of these…

Computation and Language · Computer Science 2024-10-14 Rohan Ajwani , Shashidhar Reddy Javaji , Frank Rudzicz , Zining Zhu

Large language models (LLMs) are capable of solving a wide range of tasks, yet they have struggled with reasoning. To address this, we propose $\textbf{Additional Logic Training (ALT)}$, which aims to enhance LLMs' reasoning capabilities by…

Machine Learning · Computer Science 2024-12-24 Terufumi Morishita , Gaku Morio , Atsuki Yamaguchi , Yasuhiro Sogawa

Large Language Models (LLMs) achieve impressive performance in a wide range of tasks, even if they are often trained with the only objective of chatting fluently with users. Among other skills, LLMs show emergent abilities in mathematical…

Computation and Language · Computer Science 2024-06-12 Flavio Petruzzellis , Alberto Testolin , Alessandro Sperduti

Large language models (LLMs) have shown exceptional proficiency in natural language processing but often fall short of generating creative and original responses to open-ended questions. To enhance LLM creativity, our key insight is to…

Computation and Language · Computer Science 2024-08-09 Li-Chun Lu , Shou-Jen Chen , Tsung-Min Pai , Chan-Hung Yu , Hung-yi Lee , Shao-Hua Sun

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…

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…

Computation and Language · Computer Science 2024-04-16 Spencer M. Seals , Valerie L. Shalin