Encyclopedic articles generated entirely from the parametric memory of large
language models — no retrieval — released as a benchmark for studying LLM
factuality, unverifiability, and subject-choice behavior at scale.
This dataset accompanies the paper
"LLMpedia: A Transparent Framework to Materialize an LLM's Encyclopedic
Knowledge at Scale" (Saeed & Razniewski, 2026), arXiv:2603.24080.
Benchmarks like MMLU suggest frontier models are near… See the full description on the dataset page:
https://huggingface.co/datasets/Knowledge-aware-AI/LLMpedia.
