mlsanityData to 14 Oct 2026

ConfHit: Conformal Generative Design with Oracle Free Guarantees

arXiv 2603.07371 ↗First posted 7 Mar 2026cs.LG cs.AI stat.APcited by 1

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Abstract (arXiv)

The success of deep generative models in scientific discovery requires not only the ability to generate novel candidates but also reliable guarantees that these candidates indeed satisfy desired properties. Recent conformal-prediction methods offer a path to such guarantees, but its application to generative modeling in drug discovery is limited by budget constraints, lack of oracle access, and distribution shift. To this end, we introduce ConfHit, a distribution-free framework that provides validity guarantees under these conditions. ConfHit formalizes two central questions: (i) Certification: whether a generated batch can be guaranteed to contain at least one hit with a user-specified confidence level, and (ii) Design: whether the generation can be refined to a compact set without weakening this guarantee. ConfHit leverages weighted exchangeability between historical and generated samples to eliminate the need for an experimental oracle, constructs multiple-sample density-ratio weighted conformal p-value to quantify statistical confidence in hits, and proposes a nested testing procedure to certify and refine candidate sets of multiple generated samples while maintaining statistical guarantees. Across representative generative molecule design tasks and a broad range of methods, ConfHit consistently delivers valid coverage guarantees at multiple confidence levels while maintaining compact certified sets, establishing a principled and reliable framework for generative modeling.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 29 of its 55 references that are in the map. First posted on arXiv 7 Mar 2026.

Builds on

29 of 55 references.

References · 29

  1. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,163
  2. 2021E(n) Equivariant Graph Neural Networkscited by 965
  3. 2016Automatic chemical design using a data-driven continuous representation of moleculescited by 765
  4. 2019Conformal Prediction Under Covariate Shiftcited by 519
  5. 2019Analyzing Learned Molecular Representations for Property Predictioncited by 375
  6. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 313
  7. 2021Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlcited by 271
  8. 2021Crystal Diffusion Variational Autoencoder for Periodic Material Generationcited by 270
  9. 2020Hierarchical Generation of Molecular Graphs using Structural Motifscited by 208
  10. 20233D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Predictioncited by 177
  11. 2023Conformal Language Modelingcited by 170
  12. 2021Testing for Outliers with Conformal p-valuescited by 134
17 more
  1. 2020ProGen: Language Modeling for Protein Generationcited by 128
  2. 2023MatterGen: a generative model for inorganic materials designcited by 98
  3. 2024DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Designcited by 88
  4. 2022Selection by Prediction with Conformal p-valuescited by 69
  5. 2022Conformal Prediction Under Feedback Covariate Shift for Biomolecular Designcited by 54
  6. 2024MolCRAFT: Structure-Based Drug Design in Continuous Parameter Spacecited by 48
  7. 2023Model-free selective inference under covariate shift via weighted conformal p-valuescited by 29
  8. 2024Non-Exchangeable Conformal Language Generation with Nearest Neighborscited by 21
  9. 2021The Balancing Act in Causal Inferencecited by 20
  10. 2020A Two-Sample Conditional Distribution Test Using Conformal Prediction and Weighted Rank Sumcited by 19
  11. 2021Deep Generative Modeling for Protein Designcited by 17
  12. 2024Optimized Conformal Selection: Powerful Selective Inference After Conformity Score Optimizationcited by 14
  13. 2019Concepts and Applications of Conformal Prediction in Computational Drug Discoverycited by 13
  14. 2023Conformal Drug Property Prediction with Density Estimation under Covariate Shiftcited by 13
  15. 2024Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filteringcited by 10
  16. 2025Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regressioncited by 10
  17. 2025Reliable algorithm selection for machine learning-guided designcited by 2

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Citing papers per year: 2026: 1.

1 paper.

  1. 2026Conformal Selective Prediction with General Risk Controlcited by 12