5 papers
Listen, See and Track: Spatio-Temporal Audio-Visual Sound Event Reasoning for Omni-Modal Language Models
Zhi Zeng, Cheng Zhang, Zesheng Yang +9
Understanding dynamic sound sources requires jointly determining what produces a sound, where the source is located, and how it moves over time. Yet existing audio-language models…
The Deliberative Illusion: Diagnosing Factual Attrition and Stance Homogenization in Multi-Agent LLM Deliberation
Herun Wan, Jiaying Wu, Minnan Luo +4
Multi-agent LLM systems often treat consensus as evidence of successful interaction. For deliberative problems, however, reliability depends on whether agents preserve the facts an…
From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the Wild
Zhi Zeng, Yifei Yang, Jiaying Wu +5
The rise of micro-videos has reshaped how misinformation spreads, amplifying its speed, reach, and impact on public trust. Existing benchmarks typically focus on a single deception…
DiFaR: Enhancing Multimodal Misinformation Detection with Diverse, Factual, and Relevant Rationales
Herun Wan, Jiaying Wu, Minnan Luo +3
Generating textual rationales from large vision-language models (LVLMs) to support trainable multimodal misinformation detectors has emerged as a promising paradigm. However, its e…
Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection
Herun Wan, Jiaying Wu, Minnan Luo +2
Misinformation detection models often rely on superficial cues (i.e., \emph{shortcuts}) that correlate with misinformation in training data but fail to generalize to the diverse an…