Verification
A process of examining a generated claim or answer through additional evidence, tests, comparisons, or another means of checking it.
Example
A numerical result in a model's answer is recomputed using a different method and compared with the original conclusion.
Distinctions and cautions
Verification is the process of checking an output. It differs from Self-correction Failure, which concerns what happens when a model fails to revise an error after review or correction is expected. Verification does not guarantee correctness; looking only at a model's internal confidence is not necessarily verification in the sense used here.
Evidence
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Chain-of-Verification Reduces Hallucination in Large Language Models
- Title
- Chain-of-Verification Reduces Hallucination in Large Language Models
- Author / organization
- Dhuliawala et al.
- Year
- 2024
- Source type / publication status
- Findings ACL peer-reviewed research; published
- Supported concepts / claim context
- Verification; mitigation of hallucination.
- Scope and limitations
- Self-/model-based verification does not guarantee external ground truth.
- Access / version note
- Published ACL Findings.
- Recorded official URL / DOI / identifier
- DOI:
10.18653/v1/2024.findings-acl.212(DOI resolver)
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation
- Title
- FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation
- Author / organization
- Min et al.
- Year
- 2023
- Source type / publication status
- EMNLP peer-reviewed research; published
- Supported concepts / claim context
- Factuality, Verification, claim-level support.
- Scope and limitations
- Mainly biographies and long-form generation; depends on the quality of reference knowledge sources.
- Access / version note
- Published EMNLP.
- Recorded official URL / DOI / identifier
- DOI:
10.18653/v1/2023.emnlp-main.741(DOI resolver)
Verify with Caution: The Pitfalls of Relying on Imperfect Factuality Metrics
- Title
- Verify with Caution: The Pitfalls of Relying on Imperfect Factuality Metrics
- Author / organization
- Godbole & Jia
- Year
- 2025
- Source type / publication status
- Findings ACL peer-reviewed research; published
- Supported concepts / claim context
- Limits of verification; disagreement among factuality metrics.
- Scope and limitations
- Depends on the factuality metrics and datasets studied.
- Access / version note
- Published ACL Findings.
- Recorded official URL / DOI / identifier
- DOI:
10.18653/v1/2025.findings-acl.1175(DOI resolver)