state.of.mind.

Large language models today have a basic problem: they tend to treat information as equally valid if it appears often enough in their training data. They don’t do a good job distinguishing high-quality evidence from low-quality or biased sources. This leads to several recurring issues: * They confidently state things...

Epistemic status: Conceptual architecture proposal developed through extended discussion and self-critique. Implementation details remain speculative. Improving Truth-Seeking in LLMs: An Internal Verified Knowledge Base with Ratcheted Multi-Track Confidence Current large language models are inherently relativistic: they weight evidence by statistical prevalence rather than by quality. This produces four persistent failure...