10 citations · 31 across the 18 of their papers we have counts for
18 papers
Research Knowledge Graphs: the Shifting Paradigm of Scholarly Information Representation
Matthäus Zloch, Danilo Dessì, Jennifer D'Souza +8
Sharing and reusing research artifacts, such as datasets, publications, or methods is a fundamental part of scientific activity, where heterogeneity of resources and metadata and t…
YESciEval: Robust LLM-as-a-Judge for Scientific Question Answering
Jennifer D'Souza, Hamed Babaei Giglou, Quentin Münch
Large Language Models (LLMs) drive scientific question-answering on modern search engines, yet their evaluation robustness remains underexplored. We introduce YESciEval, an open-so…
SemEval-2025 Task 5: LLMs4Subjects -- LLM-based Automated Subject Tagging for a National Technical Library's Open-Access Catalog
Jennifer D'Souza, Sameer Sadruddin, Holger Israel +2
We present SemEval-2025 Task 5: LLMs4Subjects, a shared task on automated subject tagging for scientific and technical records in English and German using the GND taxonomy. Partici…
LLMs4SchemaDiscovery: A Human-in-the-Loop Workflow for Scientific Schema Mining with Large Language Models
Sameer Sadruddin, Jennifer D'Souza, Eleni Poupaki +7
Extracting structured information from unstructured text is crucial for modeling real-world processes, but traditional schema mining relies on semi-structured data, limiting scalab…
OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignment
Hamed Babaei Giglou, Jennifer D'Souza, Oliver Karras +1
Ontology Alignment (OA) is fundamental for achieving semantic interoperability across diverse knowledge systems. We present OntoAligner, a comprehensive, modular, and robust Python…
Instruction Finetuning for Leaderboard Generation from Empirical AI Research
Salomon Kabongo, Jennifer D'Souza
This study demonstrates the application of instruction finetuning of pretrained Large Language Models (LLMs) to automate the generation of AI research leaderboards, extracting (Tas…