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Research questionHow can audio-video diffusion models preserve intended conditioning when biased cross-modal attention reroutes semantics?In audio-video diffusion generation, cross-attention among text, audio, and video can route semantics bidirectionally rather than respecting intended conditioning. Learned biases may cause one modality to override prompts, producing visually canonical but semantically incorrect outputs.
AI
Audio & Speech Processing
Diffusion Models
Mechanistic Interpretability
Multimodal Models
Video Generation
Latest papersRecent research connected to this question, newest first.The Attention Triangle in Audio-Video ModelsThe study analyzes the three cross-attention edges among text, audio, and video, including bidirectional influence between audio and video. It uses attention-derived signals to diagnose and induce leakage under controlled conditions and applies inference-time interventions; experiments report improved semantic grounding while preserving generation quality.research paper · Sep 3, 2026
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