arXiv (All)
open access
From Static to Dynamic: On-Policy Distillation from Image to Video Diffusion Models
On-policy distillation (OPD) specializes pretrained video diffusion models through teacher supervision along the student's own generation trajectory. Although large video models are natural teachers, developing specialized video experts can require costly video data and training, while querying them
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation#182755
- AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation#180694
- Progressive-View On-Policy Distillation for Regional-to-Global Transfer in Multimodal LLMs#1116664
- UnStep: Training-Free Acceleration of Causal Video Diffusion with Fewer Steps Than Distillation#1116849
- Towards extreme video compression using general world knowledge#1091934
Record · ID 1128644
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive