1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2025
GSAP-ERE: Fine-Grained Scholarly Entity and Relation Extraction Focused on Machine Learning
Wolfgang Otto, Lu Gan, Sharmila Upadhyaya +2
Research in Machine Learning (ML) and AI evolves rapidly. Information Extraction (IE) from scientific publications enables to identify information about research concepts and resou…
cs.CL2025★ 1 cited
Hidden Entity Detection from GitHub Leveraging Large Language Models
Lu Gan, Martin Blum, Danilo Dessi +3
Named entity recognition is an important task when constructing knowledge bases from unstructured data sources. Whereas entity detection methods mostly rely on extensive training d…
cs.CL2023
GSAP-NER: A Novel Task, Corpus, and Baseline for Scholarly Entity Extraction Focused on Machine Learning Models and Datasets
Wolfgang Otto, Matthäus Zloch, Lu Gan +2
Named Entity Recognition (NER) models play a crucial role in various NLP tasks, including information extraction (IE) and text understanding. In academic writing, references to mac…