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Conformal factuality guarantees

Conformal factuality guarantees are statistical assurances, derived from conformal prediction frameworks, that mathematically bound the probability of factual errors or hallucinations in outputs generated by machine learning models such as large language models. By calibrating predictions against a holdout set of verified data, this approach provides finite-sample coverage guarantees that ensure generated claims, retained subclaims, or response sets meet a pre-specified confidence level of factual correctness. Rather than altering underlying model parameters through retraining, systems enforcing conformal factuality guarantees typically operate as post-generation or constrained decoding mechanisms, utilizing uncertainty quantification to filter out unreliable assertions or progressively back off to more conservative, defensible statements.

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Language Models with Conformal Factuality Guarantees

Language Models with Conformal Factuality Guarantees

Christopher Mohri, Tatsunori Hashimoto

OrganizationsAllen Institute for AIUniversity of California, San Diego

Why you should read this

Proposes a conformal prediction framework that provides rigorous statistical correctness guarantees for black-box language model outputs by progressively pruning uncertain sub-claims while preserving most generated content.

Large language models demonstrate impressive capabilities across diverse tasks yet can generate content unfaithful to external knowledge sources.To enforce controllable generation,this work introduces post-generation techniques for constrained decoding crafted specifically as defensible guards.We introduce SENSE,a framework leveraging span-level evidence to align outputs with desired alignment criteria.Rather than enforcing token-level constraints directly over entire vocabularies,SENSE operates through differentiable integration within multimodal retrieval settings,and further demonstrates how regulatory signals interact.In extensive experiments spanning three datasets,two scientific benchmarks,guided narrative completion,and factor verification pipelines grounded via Wikidata concepts.

Added

2026-10-02