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New AI framework Chain of Modality fixes multimodal model paradox where single-input systems outperform multi-sensory ones
arXiv cs.CV · April 17, 2026
AI Summary
- •Omni-MLLMs that integrate multiple sensory inputs underperform compared to unimodal baselines, revealing a critical flaw in current multimodal AI systems
- •Problem identified: static fusion topologies cause positional bias in sequential inputs and alignment traps in interleaved formats that distort attention processing
- •Chain of Modality (CoM) framework proposed as solution, dynamically switching between parallel, sequential, and interleaved input pathways to eliminate structural biases
- •CoM employs task-aligned cognitive execution with dual pathways for more flexible and context-aware multimodal processing
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