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Can We Read the Mind of an Audio LLM? A Verbalizable, Multilingual Middle-Layer Workspace
An audio language model is a black box in a specific way: we see what it says, never what it works out on the way there, and chain-of-thought monitoring helps only if the model writes its reasoning down. Reading a base Qwen3-Omni with a logit lens at the audio-token positions, we find that the answer to a spoken question becomes legible - in words - in the model's middle layers, before it emits any token. Five findings follow. (1) The readout carries concepts in neither the question, the options, nor the model's own transcription: on a clip whose verbatim transcription is empty garbling, it re
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T06:17:28.000Z
First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.