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The emergence of large language models (LLMs) has revolutionized the capabilities of text comprehension and generation. Multi-modal generation attracts great attention from both the industry and academia, but there is little work on…

Information Retrieval · Computer Science 2024-04-16 Xiaoteng Shen , Rui Zhang , Xiaoyan Zhao , Jieming Zhu , Xi Xiao

The recent surge of Large Language Models (LLMs) has led to claims that they are approaching a level of creativity akin to human capabilities. This idea has sparked a blend of excitement and apprehension. However, a critical piece that has…

Computation and Language · Computer Science 2025-07-03 Antoine Bellemare-Pepin , François Lespinasse , Philipp Thölke , Yann Harel , Kory Mathewson , Jay A. Olson , Yoshua Bengio , Karim Jerbi

Large Language Models (LLMs) have demonstrated remarkable in-context learning capabilities, enabling flexible utilization of limited historical information to play pivotal roles in reasoning, problem-solving, and complex pattern recognition…

Machine Learning · Computer Science 2025-03-31 Zhonglin Jiang , Qian Tang , Zequn Wang

The field of Artificial Intelligence (AI) continues to drive transformative innovations, with significant progress in conversational interfaces, autonomous vehicles, and intelligent content creation. Since the launch of ChatGPT in late…

Computation and Language · Computer Science 2025-01-13 Hussain Ahmad , Diksha Goel

Using tools by Large Language Models (LLMs) is a promising avenue to extend their reach beyond language or conversational settings. The number of tools can scale to thousands as they enable accessing sensory information, fetching updated…

Information Retrieval · Computer Science 2024-12-06 Mohammad Kachuee , Sarthak Ahuja , Vaibhav Kumar , Puyang Xu , Xiaohu Liu

Large language models (LLMs) are now being used in a wide variety of contexts, including as creativity support tools (CSTs) intended to help their users come up with new ideas. But do LLMs actually support user creativity? We hypothesized…

Human-Computer Interaction · Computer Science 2024-05-14 Barrett R. Anderson , Jash Hemant Shah , Max Kreminski

In commonsense generation, given a set of input concepts, a model must generate a response that is not only commonsense bearing, but also capturing multiple diverse viewpoints. Numerous evaluation metrics based on form- and content-level…

Computation and Language · Computer Science 2025-06-03 Tianhui Zhang , Bei Peng , Danushka Bollegala

Large Language Models (LLMs), such as ChatGPT, are increasingly leveraged for generating both traditional software code and spreadsheet logic. Despite their impressive generative capabilities, these models frequently exhibit critical issues…

Software Engineering · Computer Science 2025-11-27 Simon Thorne , Advait Sarkar

The widespread adoption of Large Language Models (LLMs) and publicly available ChatGPT have marked a significant turning point in the integration of Artificial Intelligence (AI) into people's everyday lives. This study examines the ability…

Computation and Language · Computer Science 2025-10-28 Sandeep Kumar , Tirthankar Ghosal , Vinayak Goyal , Asif Ekbal

Scientific idea generation is central to discovery, requiring the joint satisfaction of novelty and scientific soundness. Unlike standard reasoning or general creative generation, scientific ideation is inherently open-ended and…

As Large Language Models (LLMs) and other forms of Generative AI permeate various aspects of our lives, their application for learning and education has provided opportunities and challenges. This paper presents an investigation into the…

Computers and Society · Computer Science 2023-06-06 Daniel Leiker , Sara Finnigan , Ashley Ricker Gyllen , Mutlu Cukurova

Large Language Models (LLMs) have been widely used to support ideation in the writing process. However, whether generating ideas with the help of LLMs leads to idea fixation or idea expansion is unclear. This study examines how different…

Human-Computer Interaction · Computer Science 2025-05-06 Peinuan Qin , Chi-Lan Yang , Jingshu Li , Jing Wen , Yi-Chieh Lee

Reasoning based on Large Language Models (LLMs) has garnered increasing attention due to outstanding performance of these models in mathematical and complex logical tasks. Beginning with the Chain-of-Thought (CoT) prompting technique,…

Artificial Intelligence · Computer Science 2025-11-27 Yuto Suzuki , Farnoush Banaei-Kashani

Although large language models (LLMs) have demonstrated impressive ability in code generation, they are still struggling to address the complicated intent provided by humans. It is widely acknowledged that humans typically employ planning…

Software Engineering · Computer Science 2025-10-21 Xue Jiang , Yihong Dong , Lecheng Wang , Zheng Fang , Qiwei Shang , Ge Li , Zhi Jin , Wenpin Jiao

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

This study investigates the reliability of code generation by Large Language Models (LLMs), focusing on identifying and analyzing defects in the generated code. Despite the advanced capabilities of LLMs in automating code generation,…

Software Engineering · Computer Science 2024-08-27 Ali Mohammadi Esfahani , Nafiseh Kahani , Samuel A. Ajila

The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the entire design and manufacturing workflow. Specifically, we…

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

We present Thinking with Generated Images, a novel paradigm that fundamentally transforms how large multimodal models (LMMs) engage with visual reasoning by enabling them to natively think across text and vision modalities through…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Ethan Chern , Zhulin Hu , Steffi Chern , Siqi Kou , Jiadi Su , Yan Ma , Zhijie Deng , Pengfei Liu

Materials design often relies on human-generated hypotheses, a process inherently limited by cognitive constraints such as knowledge gaps and limited ability to integrate and extract knowledge implications, particularly when…