2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.AI2026
APOLO: Automatic Prompt Optimization for Ontology Learning
Huu Tan Mai, Roman Kochnev, Cuong Xuan Chu +3
Ontology Learning (OL) from text has advanced with the emergence of Large Language Models (LLMs), but it remains challenging due to the limited availability of annotated training d…
cs.LG2026
Scalable GNN-based Knowledge Graph Representation Learning with Efficient Message Passing
Huu Tan Mai, Cuong Xuan Chu, Heiko Paulheim +1
Graph neural networks (GNNs) excel at representation learning on Knowledge Graphs (KGs), achieving stateof-the-art performance on tasks like link prediction or entity classificatio…
cs.CL2024★ 2 cited
Do LLMs Really Adapt to Domains? An Ontology Learning Perspective
Huu Tan Mai, Cuong Xuan Chu, Heiko Paulheim
Large Language Models (LLMs) have demonstrated unprecedented prowess across various natural language processing tasks in various application domains. Recent studies show that LLMs…