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ReVR: Dual-Path Concept Reasoning for Multimodal Fake News Detection — arXiv:2609.33195

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.33195
License (as archived): CC0-1.0
Archived: 2026-10-08T00:18:23.584Z
SHA-256 of the archived text: ddd00234b2afb8b19495711202d2f0e980ca88d2f0e6dce8c5118b8937c9d5b4
Stable URL of this page: https://metraipolis.com/documento/dc_66cd632ece99

How to cite

ReVR: Dual-Path Concept Reasoning for Multimodal Fake News Detection — arXiv:2609.33195 — arXiv (en), https://arxiv.org/abs/2609.33195 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_66cd632ece99 (Metraipolis archive dc_66cd632ece99, sha256 ddd00234b2afb8b19495711202d2f0e980ca88d2f0e6dce8c5118b8937c9d5b4)

BibTeX

@misc{dc66cd632ece99,
  title = {ReVR: Dual-Path Concept Reasoning for Multimodal Fake News Detection — arXiv:2609.33195},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.33195},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_66cd632ece99; sha256 ddd00234b2afb8b19495711202d2f0e980ca88d2f0e6dce8c5118b8937c9d5b4},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.33195. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Vision-language models (VLMs) support multimodal fake news detection (FND) by producing explicit analyses. Recent methods further improve interpretability by organizing verification knowledge into explicit concepts. However, two questions remain: how to improve the reliability and applicability of verification concepts, and how to effectively apply reusable concepts to verify unseen news. We propose \textbf{ReVR}, a dual-path reasoning framework that constructs and applies reusable verification concepts for multimodal fake news detection. An agentic workflow grounds and consolidates candidate concepts, while statistical profiles characterize their historical behavior. During inference, a coverage-oriented path aggregates evidence from the complete concept library using a trainable encoder, while a query-focused path prompts a frozen VLM to reason over selected concepts and their observations. A learned conflict resolver selects between the two predictions when they disagree. Experiments on fake news benchmarks demonstrate the effectiveness of the method regarding detection performance and generalizability.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-29 in cs.MM).
Categorie arXiv: Multimedia (cs.MM).
Pagina del lavoro: https://arxiv.org/abs/2609.33195 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T23:55:48.880Z dalla pagina https://arxiv.org/catchup/cs.MM/2026-09-29?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).