NVlabs / NVlabs/FastGen

Support for OPSD-V

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Python
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Description

Hi FastGen team,

Thank you for releasing this great framework!

We recently released [OPSD-V: On-Policy Self-Distillation for Post-Training Few-Step Autoregressive Video Generators](https://arxiv.org/abs/2607.08766). OPSD-V performs self-distillation under the student's actual inference-time rollout and KV cache, helping reduce error accumulation and motion degradation in long autoregressive video generation while preserving fast few-step inference.

Since FastGen already supports methods such as Self-Forcing and CausVid, we believe OPSD-V could also be relevant to this framework. Would you be interested in supporting OPSD-V or discussing a possible integration? We would be happy to contribute and provide implementation details.

Thank you!

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
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  3. Fork the repository and make your change on a branch.
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Research direction

Start by reading the linked OPSD-V paper, project page, and implementation, then compare its inference-time rollout and KV-cache approach with FastGen's existing Self-Forcing and CausVid support. Done would require an agreed integration scope and working OPSD-V support, but this issue does not identify files, tests, or a concrete acceptance criterion.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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