Zero-cost epistemic uncertainty quantification and hallucination detection for LLMs. Spanda estimates how uncertain a model is without resampling, which makes it cheap enough to run on every response instead of only on samples.
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Attach an uncertainty estimate to each generation and route low-confidence ones for review.
Get a confidence signal without generating multiple samples per query.
Track uncertainty drift over time as inputs change.
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