How do you detect hallucinations in production?
hardAnswer
- (1) Retrieval-grounded: for RAG systems, verify each claim against retrieved context via NLI or LLM-judge; flag unsupported claims.
- (2) Self-consistency: sample K completions; disagreement → uncertainty → likely hallucination.
- (3) Verification tools: fact-check via web search, code execution, calculator.
- (4) Uncertainty signals: high token-level perplexity often correlates with hallucination.
- (5) User feedback loops: log 'incorrect' flags and cluster them.
- Combine multiple signals for reliability.
- No single method is perfect.
Check yourself — multiple choice
- Impossible to detect
- Retrieval-grounded verification + self-consistency + tools + token-perplexity + user feedback — combine multiple signals
- Only user reports
- Solved by higher temperature
Hallucination detection: RAG verification + self-consistency + tools + perplexity + feedback.
#hallucinations#reliability#evaluation
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