3 citations · 3 across the 11 of their papers we have counts for
6 papers · 1 filter
Do General NLP Embeddings Capture Ontological Reasoning?
Hamed Babaei Giglou, Jennifer D'Souza, Sören Auer
General-purpose NLP embedding models perform well on linguistic tasks, but their ability to capture symbolic ontological structure remains unclear. We introduce AVA, a systematic f…
NFDI4DS Shared Tasks for Scholarly Document Processing
Raia Abu Ahmad, Rana Abdulla, Tilahun Abedissa Taffa +18
Shared tasks are powerful tools for advancing research through community-based standardised evaluation. As such, they play a key role in promoting findable, accessible, interoperab…
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…
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…
LLMs4OL 2024 Overview: The 1st Large Language Models for Ontology Learning Challenge
Hamed Babaei Giglou, Jennifer D'Souza, Sören Auer
This paper outlines the LLMs4OL 2024, the first edition of the Large Language Models for Ontology Learning Challenge. LLMs4OL is a community development initiative collocated with…
Scholarly Question Answering using Large Language Models in the NFDI4DataScience Gateway
Hamed Babaei Giglou, Tilahun Abedissa Taffa, Rana Abdullah +4
This paper introduces a scholarly Question Answering (QA) system on top of the NFDI4DataScience Gateway, employing a Retrieval Augmented Generation-based (RAG) approach. The NFDI4D…