Hallucination & Off-Brand Detection
Two different problems that both need post-generation classifiers.
Hallucination Detection Pipeline
| METHOD | HOW | COST | CATCHES |
|---|---|---|---|
| Citation check | Every claim must reference a retrieved chunk | Free (string match) | Ungrounded claims |
| Claim extraction + verification | LLM extracts claims, checks each vs source | ~1 LLM call per response | Subtle misstatements |
| Self-consistency | Generate 3x with temperature > 0. Flag divergent answers | 3x generation cost | Low-confidence answers |
| Programmatic | Verify numbers/dates/prices against source DB directly | Free (DB query) | Numerical hallucinations |
Off-Brand Detection
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