Kimi-Audio

IAAN: Training-free neuron amplification improves acoustic perception in large audio-language models

Researchers introduce IAAN (Identifying and Amplifying Acoustic Neurons), a training-free, label-free inference-time method that improves non-semantic speech attribute recognition in large audio-language models by identifying and amplifying specific feed-forward neurons in the audio encoder. The method scores neurons by contrasting activations on real audio versus noise references, then amplifies the top-scoring neurons at inference. Across ten non-semantic speech attributes, IAAN yields accuracy gains of 25.7 points on Audio-Flamingo-3, 21.4 on Qwen2.5-Omni, and 9.7 on Kimi-Audio without any retraining. The work establishes that encoder-side, neuron-level intervention is substantially more effective than post-encoder or language-model-side interventions for acoustic perception.