Low-Resource Guidance for Controllable Latent Audio Diffusion
Generative audio requires fine-grained controllable outputs, yet most existing methods require model retraining on specific controls or inference-time controls (\textit{e.g.}, guidance) that can also be computationally demanding. By examining the bottlenecks of existing guidance-based controls, in particular their high cost-per-step due to decoder backpropagation, we introduce a guidance-based approach through selective TFG and Latent-Control Heads (LatCHs), which enables controlling latent audio diffusion models with low computational overhead. LatCHs operate directly in latent space, avoiding the expensive decoder step, and requiring minimal training resources (7M parameters and $\appro...
| Authors | Zachary Novack, Zack Zukowski, CJ Carr et al. |
|---|---|
| Primary category | cs.SD |
| Published | 4 March 2026 |
| Last updated at source | 4 March 2026 |
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