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README.md
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---
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license:
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tags:
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library_name: pytorch
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---
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Q_θ serves as both a re-ranker (best-of-K) and a gradient signal for guided generation on top of frozen priors (RFdiffusion, PXDesign, Proteina-ComplexA) via Langevin, SMC, TDS, or classifier guidance.
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This repository accompanies the paper *AlloGen:
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## Installation
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primaryClass = {q-bio.BM}
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}
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```
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## License
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MIT — see [`LICENSE`](LICENSE).
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license: apache-2.0
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tags:
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- protein-design
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- allosteric
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- state-selectivity
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- guided-generation
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- rfdiffusion
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- pxdesign
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- proteina
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library_name: pytorch
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---
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Q_θ serves as both a re-ranker (best-of-K) and a gradient signal for guided generation on top of frozen priors (RFdiffusion, PXDesign, Proteina-ComplexA) via Langevin, SMC, TDS, or classifier guidance.
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This repository accompanies the paper *AlloGen: AlloGen: Conformation-Selective Binder Generation with Differential State Scoring* (arXiv 2026).
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## Installation
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primaryClass = {q-bio.BM}
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}
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```
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