Germline-absorbing discrete diffusion uses the germline sequence as the absorbing state to reduce germline bias in antibody modeling, raising non-germline residue prediction accuracy from 26% to 46% and improving conditional generation tradeoffs over EvoProtGrad.
Boltz-2: Towards accurate and efficient binding affinity prediction.bioRxiv, 2025
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
CrystalBoltz performs experiment-guided posterior sampling with diffusion models on structure-factor amplitudes for protein structure determination, reporting lower RMSD and R-factors than baselines with 33x faster runtime.
citing papers explorer
-
Conditional generation of antibody sequences with classifier-guided germline-absorbing discrete diffusion
Germline-absorbing discrete diffusion uses the germline sequence as the absorbing state to reduce germline bias in antibody modeling, raising non-germline residue prediction accuracy from 26% to 46% and improving conditional generation tradeoffs over EvoProtGrad.
-
CrystalBoltz: End-to-End Protein Structure Determination via Experiment-Guided Diffusion for X-Ray Crystallography
CrystalBoltz performs experiment-guided posterior sampling with diffusion models on structure-factor amplitudes for protein structure determination, reporting lower RMSD and R-factors than baselines with 33x faster runtime.