Entity · technique

Clustered Self-Assessment

techniqueactiveclustered-self-assessment-443f9cb2·1 events·first seen Jun 3, 2026

Aliases: Clustered Self-Assessment

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Recent events (1)

5arXiv · cs.CL·Jun 3, 2026·source ↗

Clustered Self-Assessment: LLM uncertainty quantification via semantic clustering and multiple-choice self-evaluation

A new arXiv preprint proposes Clustered Self-Assessment, a method for uncertainty quantification in LLMs that groups sampled generations into semantically distinct clusters, reformats them as multiple-choice options, and uses the model's own probability assignments as confidence estimates. The approach outperforms entropy-based baselines across multiple models and datasets, achieving competitive performance with as few as two additional samples. The method is notable for directly leveraging the model's self-assessment capability rather than relying on indirect distributional signals.

Evaluation and Benchmarking AI Safety Research Clustered Self-Assessment