5 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…
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…
LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis
Hamed Babaei Giglou, Jennifer D'Souza, Sören Auer
In response to the growing complexity and volume of scientific literature, this paper introduces the LLMs4Synthesis framework, designed to enhance the capabilities of Large Languag…
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…