Hallucination

Hallucination is the production of plausible, well-formed content that has no basis in fact — a cited source that does not exist, an API method that was never defined, a file path that is invented rather than observed. The term is imperfect (confabulation is closer) but it has stuck.

It is not a bug in the ordinary sense. A Large Language Model generates likely continuations; a fluent wrong answer and a fluent right answer are equally likely-looking from inside the model. Nothing in the objective distinguishes them.

The important consequence is that fluency is not evidence, and specificity is actively misleading: a precise-sounding mechanism reads as more rigorous than an honest "not established", which is exactly the trap described in Plausible Mechanism. Humans make the same error for the same reason, which is why the mitigation is procedural rather than model-specific.

Mitigations that work are all about grounding. Give the model tools to look rather than recall — reading the file beats remembering the file. Validate identifiers against a real catalogue rather than trusting recall. Require citations that can be checked. And design so that unverifiable claims are cheap to detect: an exhaustive claim, an invented path, or a cited test file are each one command away from being falsified. See Ground Truth and Exhaustive Claim.