ElementCheck: Complexity-Aware Long-Form Text Factuality Evaluation via Sentence Elements
arXiv:2608.26118v1 Announce Type: new Abstract: Existing long-form factuality evaluation relies on the decompose-retrieve-verify pipeline. However, the pipeline suffers from noise from claim decomposition and fixed verification granularity, resulting in unreliable results. We propose ElementCheck, a complexity-aware framework that verifies long-form outputs via sentence elements. Instead of uniformly decomposing sentences into atomic sub-claims, ElementCheck extracts entity pairs that are explicitly linked through verifiable connections in the original sentence as elements, and organizes these into an element graph. The graph topology provides a structural signal for estimating sentence complexity, enabling direct verification for simple sentences and targeted element-level refinement and verification for complex ones. To support fine-grained evaluation, we construct a new benchmark FastFact-Sent by mapping isolated claims from FastFact-Bench back to their source sentences. Experiments on FastFact-Sent and two domain-specific benchmarks show ElementCheck consistently improves factuality verification across five backbone models while maintaining a favorable accuracy-cost trade-off. Further analyses demonstrate that complexity-aware verification reduces unnecessary re-verification and maintains stability across different backbones.
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[Submitted on 17 Jun 2026]
Title:ElementCheck: Complexity-Aware Long-Form Text Factuality Evaluation via Sentence Elements
View a PDF of the paper titled ElementCheck: Complexity-Aware Long-Form Text Factuality Evaluation via Sentence Elements, by Xinming Wang and 8 other authors
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Abstract:Existing long-form factuality evaluation relies on the decompose-retrieve-verify pipeline. However, the pipeline suffers from noise from claim decomposition and fixed verification granularity, resulting in unreliable results. We propose ElementCheck, a complexity-aware framework that verifies long-form outputs via sentence elements. Instead of uniformly decomposing sentences into atomic sub-claims, ElementCheck extracts entity pairs that are explicitly linked through verifiable connections in the original sentence as elements, and organizes these into an element graph. The graph topology provides a structural signal for estimating sentence complexity, enabling direct verification for simple sentences and targeted element-level refinement and verification for complex ones. To support fine-grained evaluation, we construct a new benchmark FastFact-Sent by mapping isolated claims from FastFact-Bench back to their source sentences. Experiments on FastFact-Sent and two domain-specific benchmarks show ElementCheck consistently improves factuality verification across five backbone models while maintaining a favorable accuracy-cost trade-off. Further analyses demonstrate that complexity-aware verification reduces unnecessary re-verification and maintains stability across different backbones.
Comments: 25 pages, 4 figures
Subjects:
Computation and Language (cs.CL)
Cite as: arXiv:2608.26118 [cs.CL]
(or arXiv:2608.26118v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2608.26118
arXiv-issued DOI via DataCite
Submission history
From: Xinming Wang [view email] [v1] Wed, 17 Jun 2026 16:25:19 UTC (2,063 KB)
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