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Boltzmann Generators
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boltzmann-generators-2ba45227·1 events·first seen 4d agoAliases: Boltzmann Generators
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Autoregressive Boltzmann Generators (ArBG) achieve 60%+ improvement in molecular equilibrium sampling
Researchers introduce Autoregressive Boltzmann Generators (ArBG), a framework that replaces normalizing flows in Boltzmann Generators with autoregressive models inspired by LLM architectures, circumventing invertibility constraints and enabling sequential inference-time interventions. The approach demonstrates significant improvements over flow-based models across benchmarks, particularly on larger peptide systems like the 10-residue Chignolin. The authors also release Robin, a 132M-parameter transferable model trained with ArBG that reduces zero-shot energy error on 8-residue systems by over 60% compared to prior state-of-the-art.