The many faces of GESIS
Vita
Sharmila Upadhyaya is a doctoral Student at GESIS – Leibniz Institute for the Social Sciences from November, 2022. In October 2022, she completed her Erasmus Mundus Language and Communication Technology (LCT) Master’s degree at the University of Lorraine, France and Saarland University, Germany, with a specialization in Computational Linguistics. Before that, She was working as a NLP Engineer at Ekbana Solutions in Nepal for 2 years.Research
Sharmila's research interest includes NLP, Speech Processing and Knowledge Graph.Publications
Journal article
Tong, Lin, Xu Tong, Lei Lei, Ziling Zeng, Sihong Liu, Lei Zhang, Cheng Wang, Sharmila Upadhyaya, Hongjun Yang, and Huamin Zhang. 2024. "Chinese text recognition and knowledge graph of Shen Nong Ben Cao Jing based on BERT pretrained language models." Guidelines and Standards in Chinese Medicine 2 (1): 13-20. doi: https://doi.org/10.1097/gscm.0000000000000017.
Chapter in an edited book
Otto, Wolfgang, Sharmila Upadhyaya, and Stefan Dietze. 2024. "Enhancing Software-Related Information Extraction via Single-Choice Question Answering with Large Language Models." In Natural Scientific Language Processing and Research Knowledge Graphs. NSLP 2024, edited by Georg Rehm, Stefan Dietze, Sonja Schimmler, and Frank Krüger, Lecture Notes in Computer Science 14770, 289-306. Cham: Springer Nature. doi: https://doi.org/10.1007/978-3-031-65794-8_21. https://link.springer.com/content/pdf/10.1007/978-3-031-65794-8.pdf.
Working and discussion paper
Tong, Xu, Nina Smirnova, Sharmila Upadhyaya, Ran Yu, Chao Sun, Jack Culbert, Wolfgang Otto, and Philipp Mayr. 2024. Utilizing Large Language Models for Named Entity Recognition in Traditional Chinese Medicine against COVID-19 Literature: Comparative Study. arXiv. doi: https://doi.org/10.48550/arXiv.2408.13501.
Data/Software
Upadhyaya, Sharmila. 2024. gesisDataSeachKG Resources. doi: https://doi.org/10.5281/zenodo.11070842.