How to Guide Your Language Flow
Quick summary
arXiv:2609.19356v1 Announce Type: cross Abstract: We introduce a new method to guide flow matching models. Our approach, which we call probe guidance, uses the frozen internal states of an existing diffusion model to construct a guidance signal. This works using a similar principle as autoguidance, but eliminates the need for an additional forward pass at inference time and provides a reliable path to ensure that the weak and strong model share similar dynamics. We apply and benchmark this method on continuous diffusion language models, where probe guidance sets a new state-of-the-art performa
Key takeaways
- arXiv:2609.19356v1 Announce Type: cross Abstract: We introduce a new method to guide flow matching models.
- Our approach, which we call probe guidance, uses the frozen internal states of an existing diffusion model to construct a guidance signal.
- This works using a similar principle as autoguidance, but eliminates the need for an additional forward pass at inference time and provides a reliable path to ensure that the weak and strong model share similar dynamics.
Why it matters
The value of this work lies as much in how it was tested as in the claim itself. Sample design, baselines, uncertainty and replication help separate a laboratory result from real-world impact.
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