Paper

Context-Aware Multimodal Claim Verification in Spoken Dialogues

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arXiv:2606. 11420v1 Announce Type: new Abstract: Every day, millions absorb claims from podcasts and streams that no fact-checker ever sees.

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Authors: Chaewan Chun, Delvin Ce Zhang, Dongwon Lee
Released: 2026-06-11 (28d ago)
Topic: Related to current project
Relation to my work: Read next because Context-Aware Multimodal Claim Verification in Spoken Dialogues overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, text, under, line, rate, sees, alone, fact-check. Source: arxiv cs.CL (NLP).
arXiv: 2606.11420

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