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qiz1907 / LongLive-RAG

Official Implementation of LongLive-RAG: A general retrieval-augmented framework for long video generation.

Why this job: says: rag, retrieval augmented; topics: retrieval-augmented-generation

LongLive-RAG framework overview

What it does

  • First of its kind. Among open-ended AR long video generation methods, the first to formulate self-generated latent history as content-addressable retrieval memory.
  • Plug-and-play. Works across Causal-Forcing, Self-Forcing, and LongLive with the base generator frozen.
  • Searchable history. Retrieves the most relevant past latents as extra context for each new block.
  • Window Temporal Delta Loss. Makes embeddings capture meaningful temporal change, not redundant local similarity.
  • Consistent wins. Best average VBench-Long rank across lengths and backbones.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 5 months ago
Stars
115
On GitHub
Licence
Apache-2.0
Allows business use
Downloads for
None listed
No release files
Latest version
None yet
No releases
Built with
Python
99% of the code

Is it looked after?

Contributors
0
Last 90 days
Issues
50% closed
1 still open
Pull requests
0 merged
0 waiting
Releases
None
Never published
  • No contributing guide
  • No security policy
  • No code of conduct

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More: languages, topics and project record

Languages

  • Python 99%
  • Shell 1%

Topics

  • autoregressive
  • diffusion-models
  • generative-ai
  • long-video-generation
  • pytorch
  • retrieval-augmented-generation
  • video-diffusion
  • video-diffusion-model
  • video-generation
  • wan

Project record

  • JobRAG and search
  • StatusListed
  • Commits8
  • Forks3
  • Watching2
  • Stars in 28 days+1
  • CreatedMay 31, 2026
  • First seen by usNov 7, 2026
  • CheckedNov 7, 2026

Type to search.

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