AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
FEVEROUS and AVERITEC remained limited to sentence-level facts.
“FEVEROUS (Aly et al., 2021) and AVERITEC (Schlichtkrull et al., 2023) build on FEVER but remained limited to sentence-level facts.”
From VeriScore: Evaluating the factuality of verifiable claims in long-form text generation (2024) · cites this paper as Schlichtkrull et al., 2023
FEVEROUS and AVERITEC build on FEVER.
“FEVEROUS (Aly et al., 2021) and AVERITEC (Schlichtkrull et al., 2023) build on FEVER but remained limited to sentence-level facts.”
From VeriScore: Evaluating the factuality of verifiable claims in long-form text generation (2024) · cites this paper as Schlichtkrull et al., 2023
Cited by
Sorted by citations
Epistemic Injustice in Generative AI
Kay, J., Kasirzadeh, A., & Mohamed, S. (2024) · Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1609/aies.v7i1.31671 · Cited by 76 · see citing works
VeriScore: Evaluating the factuality of verifiable claims in long-form text generation
Song, Y., Kim, Y., & Iyyer, M. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024 · doi:10.18653/v1/2024.findings-emnlp.552 · Cited by 15 · see citing works
- Authors
- Schlichtkrull, M., Guo, Z., & Vlachos, A.
- Venue
- Advances in Neural Information Processing Systems 36
- Published
- 2023
- Pages
- 65128-65167
- ISSN
- 1049-5258 (ISSN-L)
- OpenAlex
- W7133222840
- Cited by
- 19
- References
- 0
- Citations by year
- 2026: 12 · 2025: 4 · 2024: 3
- FWCI
- 14.81
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- neural information processing systems (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Keywords
- claim verification, misinformation, datasets, fact-checking, information retrieval
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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