OMGuard combines interpretation-aware fine-tuning and rationale-guided headline rewriting to detect and correct omission-based misleadingness in multimodal news previews, raising an 8B model's performance to match a 235B LVLM.
Peng Qi, Zehong Yan, Wynne Hsu, and Mong Li Lee
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
EVian decomposes vision-language model responses into three cognitive components and audits them along consistency, coherence, and accuracy axes, showing that a small curated subset outperforms much larger training sets.
citing papers explorer
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What's Left Unsaid? Detecting and Correcting Misleading Omissions in Multimodal News Previews
OMGuard combines interpretation-aware fine-tuning and rationale-guided headline rewriting to detect and correct omission-based misleadingness in multimodal news previews, raising an 8B model's performance to match a 235B LVLM.
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Evian: Towards Explainable Visual Instruction-tuning Data Auditing
EVian decomposes vision-language model responses into three cognitive components and audits them along consistency, coherence, and accuracy axes, showing that a small curated subset outperforms much larger training sets.