ARXIV:2604.04692 · MULTIMODAL FACT-CHECKING · SUBMITTED 07 APR · 20:11 UTC · FRESHNESS UNKNOWN

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Is a Picture Worth a Thousand Words? Adaptive Multimodal Fact-Checking with Visual Evidence Necessity

Jaeyoon Jung · Yejun Yoon · Kunwoo Park · arXiv

AMuFC is a multimodal fact-checking framework that adaptively uses visual evidence, improving accuracy by determining when visual information is truly necessary for claim verification.

Ship in 2-4 weeks›Score7.0Evidence unverified

Opportunity summary

Pain AMuFC is a multimodal fact-checking framework that adaptively uses visual evidence, improving accuracy by determining when visual information is truly necessary for claim verification.

Evidence 0 refs | 0 sources | 0% coverage

Blocker Evidence unverified

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PROBLEM

AMuFC is a multimodal fact-checking framework that adaptively uses visual evidence, improving accuracy by determining when visual information is truly necessary for claim verification. While recent research has progressed from text-only to multimodal fact-checking,…

METHOD

Full abstract

Automated fact-checking is a crucial task not only in journalism but also across web platforms, where it supports a responsible information ecosystem and mitigates the harms of misinformation. While recent research has progressed from text-only to multimodal fact-checking, a prevailing assumption is that incorporating visual evidence universally improves performance. In this work, we challenge this assumption and show that indiscriminate use of multimodal evidence can reduce accuracy. To address this challenge, we propose AMuFC, a multimodal fact-checking framework that employs two collaborative agents with distinct roles for the adaptive use of visual evidence: An Analyzer determines whether visual evidence is necessary for claim verification, and a Verifier predicts claim veracity conditioned on both the retrieved evidence and the Analyzer's assessment. Experimental results on three datasets show that incorporating the Analyzer's assessment of visual evidence necessity into the Verifier's prediction yields substantial improvements in verification performance. In addition to all code, we release WebFC, a newly constructed dataset for evaluating fact-checking modules in a more realistic scenario, available at https://github.com/ssu-humane/AMuFC.

RESULT

ScienceToStartup currently rates this 7.0/10 on the public viability pass. Automated fact-checking is a crucial task not only in journalism but also across web platforms, where it supports a responsible information ecosystem and mitigates…

WHY NOW

Multimodal Fact-Checking moved forward this cycle; last verified April 2026. Public score 7.0/10. Implementation evidence is present through a linked repository.

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Opportunity summary

Score7.0

PainAMuFC is a multimodal fact-checking framework that adaptively uses visual evidence, improving accuracy by determining when visual information is truly necessary for claim verification.

Evidence0 refs | 0 sources | 0% coverage

Blockerno shell-level blocker reported

Analysis summary

AMuFC is a multimodal fact-checking framework that adaptively uses visual evidence, improving accuracy by determining when visual information is truly necessary for claim verification.

VerifiedSource: PDF linkedVerifiedPaperPack: citation fields availablePartialProof: unverified proof status

Competitive landscape

AMuFC is a multimodal fact-checking framework that adaptively uses visual evidence, improving accuracy by determining when visual information is truly necessary for claim verification.

Segment

Multimodal Fact-Checking

Adoption evidence

Public code linked for build inspection

Commercial read

7.0/10 public viability

Direct

not classified

Adjacent

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Substitute

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Unknown

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Competitive landscape

AMuFC is a multimodal fact-checking framework that adaptively uses visual evidence, improving accuracy by determining when visual information is truly necessary for claim verification.

Segment

Multimodal Fact-Checking

Adoption evidence

Public code linked for build inspection

Commercial read

7.0/10 public viability

Direct

not classified

Adjacent

not classified

Substitute

not classified

Unknown

not classified

Is a Picture Worth a Thousand Words? Adaptive Multimodal Fact-Checking with Visual Evidence Necessity

Is a Picture Worth a Thousand Words? Adaptive Multimodal Fact-Checking with Visual Evidence Necessity

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