Full Paper Title: "Inverse Knowledge Search over Verifiable Reasoning: Synthesizing a Scientific Encyclopedia from a Long Chains-of-Thought Knowledge Base"
The paper explains why this matters. "Reasoning compression" is a root cause of #LLM #hallucination.
When LLMs mimic human data, they inherit this "dark matter blindness."
We had to start from first principles.
Our method: Decompress scientific reasoning.
It starts with a “Socrates Agent”.
This agent generated ~3 million first-principles questions across a curriculum of ~200 courses, from high-school to graduate level .
Next, multiple independent "solver models" generate Long Chains-of-Thought (LCoT) for each question.
To ensure high fidelity, we only keep answers verified by "cross-model answer consensus" .
This creates a massive, verifiable LCoT knowledge base.
This LCoT base powers our "Brainstorm Search Engine" .
It performs "Inverse Knowledge Search".
You stop asking "What is an Instanton?"
Instead, you retrieve all the first-principles paths that derive the concept of an Instanton.
This reveals its non-trivial connections:
Quantum tunneling in double-wells
QCD vacuum structure
Hawking radiation
4D manifolds in pure math
The "dark matter" is made visible.
This is #SciencePedia. Our "Plato Synthesizer" narrates LCoT chains into coherent articles.
The result? Articles with ~50% lower factualhallucination and significantly higher knowledge density than baseline LLMs .
#SciencePedia is now live with ~200,000 entries. Come explore.
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