RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild
Multimodal misinformation increasingly leverages visual persuasion, where repurposed or manipulated images strengthen misleading text. We introduce \textbf{RW-Post}, a post-aligned \textbf{text--image benchmark} for real-world multimodal fact-checking with \emph{auditable} annotations: each instance links the original social-media post with reasoning traces and explicitly linked evidence items derived from human fact-check articles via an LLM-assisted extraction-and-auditing pipeline. RW-Post su
Record details
Published: 11 May 2026
Source: arXiv
Category: Research
Topics: Misinformation · Transparency
Retrieved: 14 July 2026
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ethics.ai (11 May 2026), “RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild,” evidence record 4565, https://ethics.ai/record/4565 (originally published by arXiv).
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