When Does Bigger Help? A Controlled Study of LLM Scale for Ontology Learning
The discussion of "When Does Bigger Help? A Controlled Study of LLM Scale for Ontology Learning" examines how model size affects performance. Hosts conclude that task type matters more than pure scale. Smaller, dense models perform well in simple classification tasks, while larger Mixture-of-Experts (MoE) models are necessary for complex hierarchical reasoning and taxonomy discovery.