---
title: "Native Streaming AR Training"
created: 2026-06-20
updated: 2026-06-20
type: concept
tags: ["training", "autoregressive", "streaming", "causal"]
sources: ["https://arxiv.org/abs/2606.17800"]
---

# Native Streaming AR Training (原生流式自回归训练)

**Native Streaming AR Training** 是 [[maineCoon|MaineCoon]] 的核心训练范式：在训练和推理时使用**相同的因果逐块自回归 regime**，而非通过 teacher forcing 从非因果教师蒸馏。

## 核心原则

- **Chunk-by-chunk causal rollout**：每次预测一个 chunk，仅以已生成的 chunk 为条件
- **无 Teacher Forcing**：不从双向教师蒸馏流式行为——原生即流式
- **Train-inference matched**：训练和推理分布一致，消除 gap

## 关键组件

- [[self-resampling|Self-Resampling]]：以模型自身退化历史为条件
- [[flow-matching|Flow Matching]] loss
- [[audio-visual-representation-alignment|Cross-Modal Representation Alignment]] 加速

## 参考
- [[maineCoon|MaineCoon 论文]] Section 3.1
- [[self-resampling|Self-Resampling]]
- [[autoregressive-video-generation|自回归视频生成]]
- [[wan-streamer]] — 端到端流式全双工交互中的原生流式训练
