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Related papers: Large Language Models for Scientific Idea Generati…

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The spread of scientific knowledge depends on how researchers discover and cite previous work. The adoption of large language models (LLMs) in the scientific research process introduces a new layer to these citation practices. However, it…

Digital Libraries · Computer Science 2025-04-04 Andres Algaba , Vincent Holst , Floriano Tori , Melika Mobini , Brecht Verbeken , Sylvia Wenmackers , Vincent Ginis

Large Language Models (LLMs) are rapidly reshaping scientific research. We analyze these changes in multiple, large-scale datasets with 2.1M preprints, 28K peer review reports, and 246M online accesses to scientific documents. We find: 1)…

Digital Libraries · Computer Science 2026-01-21 Keigo Kusumegi , Xinyu Yang , Paul Ginsparg , Mathijs de Vaan , Toby Stuart , Yian Yin

The scientific literature's exponential growth makes it increasingly challenging to navigate and synthesize knowledge across disciplines. Large language models (LLMs) are powerful tools for understanding scientific text, but they fail to…

Computation and Language · Computer Science 2025-05-30 Abhipsha Das , Nicholas Lourie , Siavash Golkar , Mariel Pettee

Automated scientific idea generation systems have made remarkable progress, yet the automatic evaluation of idea novelty remains a critical and underexplored challenge. Manual evaluation of novelty through literature review is…

Information Retrieval · Computer Science 2025-06-30 Simra Shahid , Marissa Radensky , Raymond Fok , Pao Siangliulue , Daniel S. Weld , Tom Hope

Large language models (LLMs) have been touted to enable increased productivity in many areas of today's work life. Scientific research as an area of work is no exception: the potential of LLM-based tools to assist in the daily work of…

Software Engineering · Computer Science 2024-04-24 Mohamed Nejjar , Luca Zacharias , Fabian Stiehle , Ingo Weber

Due to an exponential increase in published research articles, it is impossible for individual scientists to read all publications, even within their own research field. In this work, we investigate the use of large language models (LLMs)…

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a…

Computation and Language · Computer Science 2023-08-29 Lixiang Yan , Lele Sha , Linxuan Zhao , Yuheng Li , Roberto Martinez-Maldonado , Guanliang Chen , Xinyu Li , Yueqiao Jin , Dragan Gašević

Conventional predictive modeling of parametric relationships in manufacturing processes is limited by the subjectivity of human expertise and intuition on the one hand and by the cost and time of experimental data generation on the other…

Computation and Language · Computer Science 2025-06-26 Kiarash Naghavi Khanghah , Anandkumar Patel , Rajiv Malhotra , Hongyi Xu

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

As networking systems become increasingly complex, achieving disruptive innovation grows more challenging. At the same time, recent progress in Large Language Models (LLMs) has shown strong potential for scientific hypothesis formation and…

Networking and Internet Architecture · Computer Science 2026-03-30 Mengrui Zhang , Bang Huang , Yunxin Xu , Haiying Huang , Luxi Zhao , Mochun Long , Qingyu Song , Qiao Xiang , Xue Liu , Jiwu Shu

Recent advancements in large language models (LLMs) demonstrate strong potential for generating novel research ideas, yet such ideas often struggle with feasibility and effectiveness. In this paper, we investigate whether augmenting LLMs…

Computation and Language · Computer Science 2026-03-03 Xiao Liu , Xinyi Dong , Xinyang Gao , Yansong Feng , Xun Pang

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

Large language models (LLMs) are introducing a paradigm shift in molecular discovery by enabling text-guided interaction with chemical spaces through natural language, symbolic notations, with emerging extensions to incorporate multi-modal…

Machine Learning · Computer Science 2025-05-23 Ziqing Wang , Kexin Zhang , Zihan Zhao , Yibo Wen , Abhishek Pandey , Han Liu , Kaize Ding

Background: Over the past few decades, the process and methodology of automated question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the…

Artificial Intelligence · Computer Science 2024-12-06 Dominic Lohr , Marc Berges , Abhishek Chugh , Michael Kohlhase , Dennis Müller

The rapid development of artificial intelligence has led to marked progress in the field. One interesting direction for research is whether Large Language Models (LLMs) can be integrated with structured knowledge-based systems. This…

Computation and Language · Computer Science 2025-05-02 Wenli Yang , Lilian Some , Michael Bain , Byeong Kang

Reasoning is an important task for large language models (LLMs). Among all the reasoning paradigms, inductive reasoning is one of the fundamental types, which is characterized by its particular-to-general thinking process and the…

Computation and Language · Computer Science 2026-04-14 Kedi Chen , Dezhao Ruan , Yuhao Dan , Yaoting Wang , Siyu Yan , Xuecheng Wu , Yinqi Zhang , Qin Chen , Jie Zhou , Liang He , Biqing Qi , Linyang Li , Qipeng Guo , Xiaoming Shi , Wei Zhang

Scientific discovery is an inherently creative and uncertain process, requiring reasoning beyond the recall of known knowledge. While many benchmarks have been proposed to evaluate large language model (LLM) performance on deep research…

Artificial Intelligence · Computer Science 2026-05-29 A. J. Lew , Y. Cao , M. J. Buehler

Novelty is a crucial criterion in the peer review process for evaluating academic papers. Traditionally, it's judged by experts or measure by unique reference combinations. Both methods have limitations: experts have limited knowledge, and…

Computation and Language · Computer Science 2025-07-17 Wenqing Wu , Chengzhi Zhang , Yi Zhao

Research ideation involves broad exploring and deep refining ideas. Both require deep engagement with literature. Existing tools focus primarily on idea broad generation, yet offer little support for iterative specification, refinement, and…

Human-Computer Interaction · Computer Science 2025-07-16 Kevin Pu , K. J. Kevin Feng , Tovi Grossman , Tom Hope , Bhavana Dalvi Mishra , Matt Latzke , Jonathan Bragg , Joseph Chee Chang , Pao Siangliulue

Large Language Models have taken the cognitive science world by storm. It is perhaps timely now to take stock of the various research paradigms that have been used to make scientific inferences about ``cognition" in these models or about…

Artificial Intelligence · Computer Science 2024-06-17 Desmond C. Ong
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