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How to Spend Your Oracle Budget: Practical Guidance for Protein Structure Prediction Models

Research Bioinformatics AI

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TL;DR - This study benchmarks oracle-budget-aware guidance methods for protein structure prediction. It finds that method effectiveness depends on budget: O3 performs best at low budgets, while FK-steering and DPO improve as budgets grow.

  • Compares O3, FK-steering, DPO, and Best K-of-N sampling under constrained oracle access.
  • Extends Optimisation Over Outputs (O3) to protein structure prediction models.
  • Evaluates guidance on calmodulin (1CLL) and E. coli aspartate transcarbamoylase (9EEH).
  • Provides practical method-selection recommendations rather than identifying one universally dominant approach.

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How to Spend Your Oracle Budget: Practical Guidance for Protein Structure Prediction Models

arXiv cs.AI Aleksandra Kalisz, Jack Simons, Krisztina Sinkovics, Noam Ghenassia, Shikha Surana, Henry Moss, Paul Duckworth 2026-08-12 arXiv:2608.12192
Public signals Semantic Scholar citations 0 · Semantic Scholar influential citations 0
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · Citations 0 · Influential citations 0 X · N/A Fetched 2026-08-17 09:43:20.437365 UTC

TL;DR - This study benchmarks oracle-budget-aware guidance methods for protein structure prediction. It finds that method effectiveness depends on budget: O3 performs best at low budgets, while FK-steering and DPO improve as budgets grow.

  • Compares O3, FK-steering, DPO, and Best K-of-N sampling under constrained oracle access.
  • Extends Optimisation Over Outputs (O3) to protein structure prediction models.
  • Evaluates guidance on calmodulin (1CLL) and E. coli aspartate transcarbamoylase (9EEH).
  • Provides practical method-selection recommendations rather than identifying one universally dominant approach.
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