RDS computes total L1 distance of N sampled embeddings from their empirical centroid on the unit hypersphere to measure semantic variability, with a probability-weighted variant that outperforms nine baselines on hallucination detection across four QA datasets and four LLMs.
Gabriel Peyré, Marco Cuturi, and 1 others
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Distance Is All You Need: Radial Dispersion for Uncertainty Estimation in Large Language Models
RDS computes total L1 distance of N sampled embeddings from their empirical centroid on the unit hypersphere to measure semantic variability, with a probability-weighted variant that outperforms nine baselines on hallucination detection across four QA datasets and four LLMs.