Mining Scholarly Big Data in the Large Language Model Era 

A PRESENTATION BY Dr. Jian Wu
Online Event via Zoom

Abstract:

Since 2023, there has been a surge of public and research interest in large language models (LLMs) and recently vision language models, which significantly shifted the paradigm of mining scholarly big data, bringing both challenges and opportunities for this ever-growing field. This paradigm shift not only significantly improves the performance of traditional metadata-centered pipelines for knowledge extraction, classification, and downstream tasks, which usually served as core components for academic digital libraries, but it also opens doors to the content-centered tasks, mining fine-grained knowledge and data, which provides deeper insights and wider applications of scholarly publications for a broader audience beyond scientific researchers. We explore LLM-based solutions for several content-centered tasks related to knowledge and data from scholarly publications, and prospect how these solutions can shed light on supporting advanced services, such as data preservation, scholarly comparison, review generation, and science dissemination. We share preliminary work in this direction, including open-access datasets and software extraction, complex table data extraction, scientific claim verification, and research reproducibility assessment.

Bio:

Dr. Jian Wu is an associate professor of Computer Science at ODU. Dr. Wu obtained his Ph.D. degree at Pennsylvania State University (Penn State) in 2011 and worked as a postdoctoral fellow with Dr. C. Lee Giles before joining ODU in 2018. Since then, his research has been supported by NSF, IMLS, DARPA, Los Alamos National Laboratory, Virginia Commonwealth, and the Open Philanthropy. Dr. Wu’s research interests include natural language processing, scholarly big data, information retrieval, digital libraries, and the science of science. He has published more than 90 peer-reviewed papers in ACM, IEEE, and AAAI venues, with best papers and nominations, in addition to his earlier publications in Astronomy and Astrophysics. Dr. Wu shared the British Computer Society Award 2021 for the Best Open Source Project with Dr. C. Lee Giles.

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