Don't Let the Video Speak: Audio-Contrastive Preference Optimization for Audio-Visual Language Models
While Audio-Visual Language Models (AVLMs) have achieved remarkable progress over recent years, their reliability is bottlenecked by cross-modal hallucination. A particularly pervasive manifestation is video-driven audio hallucination: models routinely exploit visual shortcuts to hallucinate expected sounds, discarding true auditory evidence. To counteract this deeply ingrained visual dominance, we propose Audio-Contrastive Preference Optimization (ACPO). This dual-axis preference learning framework introduces an output-contrastive objective to penalize visual descriptions masquerading as audio facts, alongside an input-contrastive objective that swaps audio tracks to explicitly penalize ...
| Authors | Ami Baid, Zihui Xue, Kristen Grauman |
|---|---|
| Primary category | cs.CV |
| Published | 15 April 2026 |
| Last updated at source | 28 August 2026 |
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