4 papers
AOR-Bench: Do Large Audio Language Models Over-Refuse Pseudo-Harmful Queries?
Jiaxi Yang, Chaewan Chun, Jason Lucas +2
Large Audio Language Models (LALMs) have demonstrated strong performance across a wide range of audio tasks. As they are increasingly deployed in real-world applications, ensuring…
Context-Aware Multimodal Claim Verification in Spoken Dialogues
Chaewan Chun, Delvin Ce Zhang, Dongwon Lee
Every day, millions absorb claims from podcasts and streams that no fact-checker ever sees. Spoken misinformation is built through conversation, where credibility comes not from fa…
When Misinformation Speaks and Converses: Rethinking Fact-Checking in Audio Platforms
Chaewan Chun, Delvin Ce Zhang, Dongwon Lee
Audio platforms have evolved beyond entertainment. They have become central to public discourse, from podcasts and radio to WhatsApp voice notes and live streams. With millions of…
MAD: A Benchmark for Multi-Turn Audio Dialogue Fact-Checking
Chaewan Chun, Lysandre Terrisse, Delvin Ce Zhang +1
Despite the growing popularity of audio platforms, fact-checking spoken content remains significantly underdeveloped. Misinformation in speech often unfolds across multi-turn dialo…