Escape the Language Prior: Mitigating Late-Stage Modality Collapse in Audio Reasoning via Modality-Aware Policy Optimization

In three linesModality-Aware Policy Optimization (MAPO) addresses late-stage modality collapse in audio-text models during RL fine-tuning. The method concentrates policy gradients on modality-critical tokens via a modality relevance mask and adds an attention penalty to sustain cross-modal grounding. MAPO achieves SOTA on several complex audio reasoning benchmarks.

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