4 citations · 8 across the 5 of their papers we have counts for
4 papers · 1 filter
How do Scaling Laws Apply to Knowledge Graph Engineering Tasks? The Impact of Model Size on Large Language Model Performance
Desiree Heim, Lars-Peter Meyer, Markus Schröder +2
When using Large Language Models (LLMs) to support Knowledge Graph Engineering (KGE), one of the first indications when searching for an appropriate model is its size. According to…
LLM-KG-Bench 3.0: A Compass for SemanticTechnology Capabilities in the Ocean of LLMs
Lars-Peter Meyer, Johannes Frey, Desiree Heim +4
Current Large Language Models (LLMs) can assist developing program code beside many other things, but can they support working with Knowledge Graphs (KGs) as well? Which LLM is off…
Benchmarking the Abilities of Large Language Models for RDF Knowledge Graph Creation and Comprehension: How Well Do LLMs Speak Turtle?
Johannes Frey, Lars-Peter Meyer, Natanael Arndt +2
Large Language Models (LLMs) are advancing at a rapid pace, with significant improvements at natural language processing and coding tasks. Yet, their ability to work with formal la…
Developing a Scalable Benchmark for Assessing Large Language Models in Knowledge Graph Engineering
Lars-Peter Meyer, Johannes Frey, Kurt Junghanns +4
As the field of Large Language Models (LLMs) evolves at an accelerated pace, the critical need to assess and monitor their performance emerges. We introduce a benchmarking framewor…