AI RESEARCH
Causal Tracing of Audio-Text Fusion in Large Audio Language Models
arXiv CS.CL
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ArXi:2603.13768v1 Announce Type: cross Despite the strong performance of large audio language models (LALMs) in various tasks, exactly how and where they integrate acoustic features with textual context remains unclear. We adapt causal tracing to investigate the internal information flow of LALMs during audio comprehension. By conducting layer-wise and token-wise analyses across DeSTA, Qwen, and Voxtral, we evaluate the causal effects of individual hidden states.