AdaLoop: Adaptive-Depth Latent Reasoning for Audio Language Models
Large audio language models answer questions about speech, sound, and music, yet their accuracy drops sharply on tasks that need fine-grained acoustic analysis. Judging which of two speakers has the higher pitch demands iterative signal-level reasoning that a content question does not. Current models spend the same computational depth on both. We introduce AdaLoop, a lightweight recurrent module that learns how many latent refinement steps a given audio--question pair requires. A shared transformer block iterates over the audio representation, guided by the question, while a learned halting mechanism exits the loop once the representation is ready. AdaLoop adds fewer than 3\% of the base ...
| Authors | Lee Seung-woo, Bowen Qi |
|---|---|
| Primary category | cs.SD |
| Published | 3 October 2026 |
| Last updated at source | 3 October 2026 |
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