# 现场音乐扩散模型：交互式扩散音乐生成器的高效微调与后训练

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-05-21 08:00
- AIHOT 分数：65
- AIHOT 链接：https://aihot.virxact.com/items/cmphd1mpc0nc9sljwqtru7d3c
- 原文链接：https://arxiv.org/abs/2605.22717

## AI 摘要

本研究探索将开源音频扩散模型改造为可在消费级硬件上运行的交互式音乐生成器。通过分析发现，传统的分块外扩扩散流程在推理时效率较低。为此，提出了现场音乐扩散模型（LMDMs），通过引入分块KV缓存优化生成过程，显著提升了推理效率。同时，LMDMs采用ARC-Forcing范式实现稳定的后训练对齐，减少了误差累积，无需依赖强化学习或奖励模型。该模型已应用于文本生成音乐、草图合成音乐及实时即兴合奏等场景，并能以“生成式延迟”效果器的形式在游戏笔记本电脑上本地运行，为音乐创作提供实时音色变换支持。

## 正文

Interactive streaming music generation promises the use of generative models for live performance and co-creation that is impossible with offline models. However, SOTA models exist in the discrete-AR regime, requiring industrial levels of compute for both training and inference. In this work, we investigate whether audio diffusion models, with their wide support in the open-source community but non-streaming bidirectional nature, can be repurposed efficiently into interactive models accessible on consumer hardware. By taking a critical look at the modern pipeline for block-wise outpainting diffusion, we identify critical inefficiencies during inference that result in strictly worse computational efficiency than their discrete-AR counterparts. We propose Live Music Diffusion Models (LMDMs), a simple modification of the generative diffusion process that recovers, and then outperforms, the inference complexity of the discrete Live Music Models (LMMs) through block-wise KV Caching. Unlike LMMs, LMDMs further enable stable post-training alignment through our novel ARC-Forcing paradigm, reducing error accumulation without any explicit RL or reward models. We demonstrate the application of LMDMs in a number of creative domains, including text-conditioned generation, sketch-based music synthesis, and jamming. We finally show how LMDMs can be used as a generative instrument in a real artist-AI collaboration, utilizing LMDMs as a "generative delay" to transform musicians' improvisation live for variable timbral effects while running locally on a consumer gaming laptop.