---
format: "aidr-story-markdown/v1"
id: "b13ccf52158ce0a59fded397351ae6cfed1a2a77f4f2e454ebd349f2441fbeef"
canonical_url: "https://aidr.today/b13ccf52?lang=en"
title: "Wave Forcing: Towards Speed-of-Light Streaming Video Generation"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-11-03T00:00:00.000Z"
category: "Research"
topics: ["inference"]
source_urls: ["https://huggingface.co/papers/2611.00859"]
summary: "Wave Forcing (WF) co-designs generation, training, and execution for continuous video output with multi-step denoising. WF uses chunk-wise causal attention to access earlier, cleaner chunks before their denoising is complete. This achieves 1F1C: one output chunk per concurrent forward round after pipeline fill."
---

# Wave Forcing: Towards Speed\-of\-Light Streaming Video Generation

> [Open the canonical story](<https://aidr.today/b13ccf52?lang=en>)

**Published:** 2026-11-03T00:00:00.000Z
**Category:** Research
**Topics:** inference

## Summary

Wave Forcing \(WF\) co\-designs generation, training, and execution for continuous video output with multi\-step denoising\. WF uses chunk\-wise causal attention to access earlier, cleaner chunks before their denoising is complete\. This achieves 1F1C: one output chunk per concurrent forward round after pipeline fill\.

## Sources

- [Story source](<https://huggingface.co/papers/2611.00859>)