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Large Language Models (LLMs) demonstrate remarkable proficiency in generating accurate and fluent text. However, they often struggle with diversity and novelty, leading to repetitive or overly deterministic responses. These limitations stem…

Computation and Language · Computer Science 2025-02-19 Arash Lagzian , Srinivas Anumasa , Dianbo Liu

Large Language Models (LLMs) have shown significant limitations in understanding creative content, as demonstrated by Hessel et al. (2023)'s influential work on the New Yorker Cartoon Caption Contest (NYCCC). Their study exposed a…

Computation and Language · Computer Science 2025-02-28 Kuan Lok Zhou , Jiayi Chen , Siddharth Suresh , Reuben Narad , Timothy T. Rogers , Lalit K Jain , Robert D Nowak , Bob Mankoff , Jifan Zhang

Human-defined creativity is highly abstract, posing a challenge for multimodal large language models (MLLMs) to comprehend and assess creativity that aligns with human judgments. The absence of an existing benchmark further exacerbates this…

Large Language Models (LLMs) have emerged with many intellectual capacities. While numerous benchmarks assess their intelligence, limited attention has been given to their ability to explore--an essential capacity for discovering new…

Artificial Intelligence · Computer Science 2025-05-13 Lan Pan , Hanbo Xie , Robert C. Wilson

In recent years, evaluating the Theory of Mind (ToM) capabilities of large language models (LLMs) has received significant attention within the research community. As the field rapidly evolves, navigating the diverse approaches and…

Computation and Language · Computer Science 2025-02-14 Karahan Sarıtaş , Kıvanç Tezören , Yavuz Durmazkeser

Large Language Models (LLMs) have shown promise in accelerating the scientific research pipeline. A key capability for this process is the ability to generate novel research ideas, and prior studies have found settings in which…

Computation and Language · Computer Science 2025-06-27 Chenglei Si , Tatsunori Hashimoto , Diyi Yang

Large language models (LLMs) have become common decision-support tools across educational and professional contexts, raising questions about how their outputs shape human critical thinking. Prior work suggests that the amount of AI…

Artificial Intelligence · Computer Science 2026-03-10 Natalie Friedman , Adelaide Nyanyo , Kevin Weatherwax , Lifei Wang , Chengchao Zhu , Zeshu Zhu , S. Joy Mountford

A key component of creativity is associative reasoning: the ability to draw novel yet meaningful connections between concepts. We introduce CREATE, a benchmark designed to evaluate models' capacity for creative associative reasoning. CREATE…

Computation and Language · Computer Science 2026-05-12 Manya Wadhwa , Tiasa Singha Roy , Harvey Lederman , Junyi Jessy Li , Greg Durrett

Large language models (LLMs) have demonstrated impressive capabilities in natural language generation. However, their output quality can be inconsistent, posing challenges for generating natural language from logical forms (LFs). This task…

Computation and Language · Computer Science 2023-09-22 Levon Haroutunian , Zhuang Li , Lucian Galescu , Philip Cohen , Raj Tumuluri , Gholamreza Haffari

As LLMs become increasingly prevalent, it is interesting to consider how ``creative'' these models can be. From cognitive science, creativity consists of at least two key characteristics: \emph{convergent} thinking (purposefulness to…

Computation and Language · Computer Science 2025-02-11 Yining Lu , Dixuan Wang , Tianjian Li , Dongwei Jiang , Sanjeev Khudanpur , Meng Jiang , Daniel Khashabi

Large Language Models (LLMs) have shown remarkable capabilities in manipulating natural language across multiple applications, but their ability to handle simple reasoning tasks is often questioned. In this work, we aim to provide a…

Computation and Language · Computer Science 2025-05-05 Alessandro Raganato , Rafael Peñaloza , Marco Viviani , Gabriella Pasi

Large language models (LLMs) have achieved remarkable progress in linguistic tasks, necessitating robust evaluation frameworks to understand their capabilities and limitations. Inspired by Feynman's principle of understanding through…

Computation and Language · Computer Science 2024-06-11 Zhiquan Tan , Lai Wei , Jindong Wang , Xing Xie , Weiran Huang

Large Language Models (LLMs) have shown remarkable capabilities in general natural language processing tasks but often fall short in complex reasoning tasks. Recent studies have explored human-like problem-solving strategies, such as…

Computation and Language · Computer Science 2023-12-19 Zhenran Xu , Senbao Shi , Baotian Hu , Jindi Yu , Dongfang Li , Min Zhang , Yuxiang Wu

Large language models (LLMs) are known to produce outputs with limited diversity. In this work, we study whether infusing random concepts in the prompts can improve the diversity of the generated outputs. To benchmark the approach, we…

Computation and Language · Computer Science 2026-01-27 Pulin Agrawal , Prasoon Goyal

This research investigates prompt designs of evaluating generated texts using large language models (LLMs). While LLMs are increasingly used for scoring various inputs, creating effective prompts for open-ended text evaluation remains…

Computation and Language · Computer Science 2024-06-28 KuanChao Chu , Yi-Pei Chen , Hideki Nakayama

Recent large language models (LLMs) have demonstrated promising capabilities in modeling real-world knowledge and enhancing knowledge-based generation tasks. In this paper, we further explore the potential of using LLMs to aid in the design…

Robotics · Computer Science 2024-11-04 Weicheng Ma , Luyang Zhao , Chun-Yi She , Yitao Jiang , Alan Sun , Bo Zhu , Devin Balkcom , Soroush Vosoughi

Large Language Models (LLMs) have shown capabilities close to human performance in various analytical tasks, leading researchers to use them for time and labor-intensive analyses. However, their capability to handle highly specialized and…

Computation and Language · Computer Science 2024-10-08 Alexander S. Choi , Syeda Sabrina Akter , JP Singh , Antonios Anastasopoulos

Large language models (LLMs) are increasingly shaping creative work and problem-solving; however, prior research suggests that they may diminish unassisted creativity. To address this tension, a coach-like LLM environment was developed that…

Human-Computer Interaction · Computer Science 2025-10-31 Alon Rosenbaum , Yigal David , Eran Kaufman , Gilad Ravid , Amit Ronen , Assaf Krebs

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

With the rapid development of Large Language Models (LLMs), a large number of machine learning models have been developed to assist programming tasks including the generation of program code from natural language input. However, how to…

Artificial Intelligence · Computer Science 2024-06-19 Debalina Ghosh Paul , Hong Zhu , Ian Bayley
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