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New benchmark MiniVer-V improves video fact-checking efficiency

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced MiniVer-V, a new benchmark designed to improve the efficiency of short-video fact-checking by identifying the minimal sufficient evidence needed for verification. The benchmark includes 195 videos with three-way verdict annotations and over 5,500 multimodal evidence units. A proposed two-layer framework separates claim-video consistency from factual determination, using a greedy search to assemble evidence until a sufficiency threshold is met, allowing for abstention when evidence is inadequate. This approach, tested with models like Claude Sonnet 4 and GPT-5.5, significantly reduces the amount of evidence required while maintaining verification accuracy. AI

IMPACT This research could lead to more efficient and accurate AI-powered fact-checking systems for video content.

RANK_REASON The item is a research paper detailing a new benchmark and methodology for video verification. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark MiniVer-V improves video fact-checking efficiency

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The item is a research paper detailing a new benchmark and methodology for video verification. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Leran Chen, Lingnan Kong, Zile Cai ·

    MiniVer-V: Identifying Minimal Sufficient Evidence for Short Video Verification

    arXiv:2610.11233v1 Announce Type: cross Abstract: A core challenge in short-video fact-checking is identifying which evidence is sufficient to support a verification conclusion. Existing approaches either give the verifier all available evidence, introducing noise, or select evid…

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