This AI Paper from Adobe and UCSD Presents DITTO: A General-Purpose AI Framework for Controlling Pre-Trained Text-to-Music Diffusion Models at Inference-Time via Optimizing Initial Noise Latents

A key challenge in text-to-music generation using diffusion models is controlling pre-trained text-to-music diffusion models at inference time. While effective, these models can only sometimes produce fine-grained and stylized musical outputs. The difficulty stems from their complexity, which usually requires sophisticated techniques for fine-tuning and manipulation to achieve specific musical styles or characteristics. This limitation […]

The post This AI Paper from Adobe and UCSD Presents DITTO: A General-Purpose AI Framework for Controlling Pre-Trained Text-to-Music Diffusion Models at Inference-Time via …

adobe ai framework ai paper ai shorts applications artificial intelligence challenge diffusion diffusion models ditto editors pick fine-grained framework general inference key music music generation noise paper sound staff tech news technology text ucsd via