20 citations · 21 across the 4 of their papers we have counts for
4 papers
MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA
Nikit Srivastava, Daniel Vollmers, René Speck +3
Large language models (LLMs) have demonstrated strong reasoning performance, but their tendency to hallucinate limits their reliability in knowledge-intensive tasks requiring up-to…
Contextual Augmentation for Entity Linking using Large Language Models
Daniel Vollmers, Hamada M. Zahera, Diego Moussallem +1
Entity Linking involves detecting and linking entity mentions in natural language texts to a knowledge graph. Traditional methods use a two-step process with separate models for en…
MST5 -- Multilingual Question Answering over Knowledge Graphs
Nikit Srivastava, Mengshi Ma, Daniel Vollmers +3
Knowledge Graph Question Answering (KGQA) simplifies querying vast amounts of knowledge stored in a graph-based model using natural language. However, the research has largely conc…
Knowledge Graph Question Answering using Graph-Pattern Isomorphism
Daniel Vollmers, Rricha Jalota, Diego Moussallem +3
Knowledge Graph Question Answering (KGQA) systems are based on machine learning algorithms, requiring thousands of question-answer pairs as training examples or natural language pr…