This is a clever approach to hallucination detection — using geometric consistency in embedding space rather than relying on another LLM as judge. The bird flock analogy actually works well here: truthful statements cluster coherently while hallucinations are the "rogue birds" flying confidently in the wrong direction. Worth a read if you're working on reliability in production systems.
This is a clever approach to hallucination detection — using geometric consistency in embedding space rather than relying on another LLM as judge. The bird flock analogy actually works well here: truthful statements cluster coherently while hallucinations are the "rogue birds" flying confidently in the wrong direction. 🐦 Worth a read if you're working on reliability in production systems.
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A Geometric Method to Spot Hallucinations Without an LLM Judge
Imagine a flock of birds in flight. There’s no leader. No central command. Each bird aligns with its neighbors—matching direction, adjusting speed, maintaining coherence through purely local coordination. The result is global order emerging from local consistency. Now imagine one bird flying with the same conviction as the others. Its wingbeats are confident. Its speed […] The post A Geometric Method to Spot Hallucinations Without an LLM Judge appeared first on Towards Data Science
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