Saurav Karmakar — accepted AI-conference papers

2026

GSAP-ERE: Fine-Grained Scholarly Entity and Relation Extraction Focused on Machine Learning

Wolfgang Otto, Lu Gan, Sharmila Upadhyaya, Saurav Karmakar, Stefan Dietze

AAAI 2026technical

Research in Machine Learning (ML) and AI evolves rapidly. Information Extraction (IE) from scientific publications enables to identify information about research concepts and resources on a large scale and therefore is a pathway to improve understanding and reproducibility of ML-related research. To

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2023

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, Saurav Karmakar, Stefan Dietze

EMNLP 2023long findings

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 machine learning models and datasets are fundamental components of various computer science publications and necessitate ac…

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