13 citations · 23 across the 23 of their papers we have counts for
5 papers · 1 filter
Diversifying Knowledge Enhancement of Biomedical Language Models using Adapter Modules and Knowledge Graphs
Juraj Vladika, Alexander Fichtl, Florian Matthes
Recent advances in natural language processing (NLP) owe their success to pre-training language models on large amounts of unstructured data. Still, there is an increasing effort t…
A Knowledge Graph Approach for Exploratory Search in Research Institutions
Tim Schopf, Nektarios Machner, Florian Matthes
Over the past decades, research institutions have grown increasingly and consequently also their research output. This poses a significant challenge for researchers seeking to unde…
From Data to Dialogue: Leveraging the Structure of Knowledge Graphs for Conversational Exploratory Search
Phillip Schneider, Nils Rehtanz, Kristiina Jokinen +1
Exploratory search is an open-ended information retrieval process that aims at discovering knowledge about a topic or domain rather than searching for a specific answer or piece of…
HealthFC: Verifying Health Claims with Evidence-Based Medical Fact-Checking
Juraj Vladika, Phillip Schneider, Florian Matthes
In the digital age, seeking health advice on the Internet has become a common practice. At the same time, determining the trustworthiness of online medical content is increasingly…
Challenges in Domain-Specific Abstractive Summarization and How to Overcome them
Anum Afzal, Juraj Vladika, Daniel Braun +1
Large Language Models work quite well with general-purpose data and many tasks in Natural Language Processing. However, they show several limitations when used for a task such as d…