A modular, finetuning-free pipeline combining RAG prompting, zero-shot embedding ensembles, and attention-based graph inference achieves top leaderboard results on the LLMs4OL 2025 ontology learning tasks.
Phoenixes at llms4ol 2024 tasks a, b, and c: Retrieval augmented generation for ontology learning,
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Heterogeneous LLM Methods for Ontology Learning (Few-Shot Prompting, Ensemble Typing, and Attention-Based Taxonomies)
A modular, finetuning-free pipeline combining RAG prompting, zero-shot embedding ensembles, and attention-based graph inference achieves top leaderboard results on the LLMs4OL 2025 ontology learning tasks.