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Cheminformatics

Active Flow Expansion for Out-of-Distribution Discovery: from Theory to Molecules

Riccardo De Santi, Bruce Lee, Cristian Perez Jensen, Kimon Protopapas, Sophia Tang, Cheng-Hao Liu, Pranam Chatterjee, Yisong Yue, Andreas Krause

Featured June 14, 2026

Original Paper

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Simply

Instead of just copying existing designs, a new method called ACTFLOW helps generative models learn to explore and create many more truly new and useful designs, like medicines, by actively asking a 'checker' if its new ideas are good.

In depth
The paper introduces Active Flow Expansion (ACTFLOW), a novel method that moves beyond standard generative models which merely match existing data distributions. Instead, ACTFLOW iteratively expands a model's generable set—the region of design space it can access with non-negligible probability—by actively exploring new, valid, out-of-distribution regions using verifier feedback and self-generated synthetic data. This enables the discovery of novel designs, such as new molecules or proteins, that are inaccessible to conventional models.

Key Takeaways

  • 1
    The concept of generable set expansion is introduced as a new learning principle for generative models, aiming to cover a larger portion of the valid design space beyond the training data.
  • 2
    ACTFLOW is a continued pre-training method that actively explores in a learned flow representation at intermediate noise levels, leveraging verifier feedback to iteratively adapt the model to self-generated synthetic data.
  • 3
    The study provides statistical learning guarantees for out-of-distribution flow modeling, demonstrating provable expansion of the generable set to cover reachable valid regions in various scientific domains.

Conceptual Flow

HIGH LEVEL
1
Methodology: Expanding Design Space

The method starts with a basic model, then repeatedly finds new good designs, checks if they are valid, and uses them to teach the model to make even more new good designs.

Basic Model
Design Checker
Learn & Expand
Model for New Designs
2
Results: Broader Discovery

The new method creates many more diverse and valid designs, like new molecules, compared to older ways that mostly stuck to what they already knew.

Old Method Designs
New Method Designs
Compare Coverage & Quality
Much Wider Range of Good Designs