TinyGiantALM, a compact 1.5B audio-language model with instruction-aware refinement, achieves 46.4% zero-shot accuracy on MMAR and outperforms models up to 8x larger in mixed-modality tasks.
Perception 31.54 39.6044.3043.62 +12.08Speaker Analysis 39.58 41.67 41.6745.83 +6.25
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TinyGiantALM: A Compact Audio-Language Model for Intent-Aware Reasoning under Resource Constraints
TinyGiantALM, a compact 1.5B audio-language model with instruction-aware refinement, achieves 46.4% zero-shot accuracy on MMAR and outperforms models up to 8x larger in mixed-modality tasks.