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cs.LG2026
DiLaDiff: Distilled Latent-Augmented Diffusion for Language Modeling
Jean-Marie Lemercier, Tomas Geffner, Karsten Kreis +3
Diffusion language models intrinsically fail to capture correlations between decoded tokens, which leads to a harsh trade-off between sampling quality and throughput. To solve this…
cs.LG2026★ 1 cited
Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute
Kieran Didi, Zuobai Zhang, Guoqing Zhou +11
Protein interaction modeling is central to protein design, which has been transformed by machine learning with applications in drug discovery and beyond. In this landscape, structu…
cs.LG2026
Latent Target Score Matching, with an application to Simulation-Based Inference
Joohwan Ko, Tomas Geffner
Denoising score matching (DSM) for training diffusion models may suffer from high variance at low noise levels. Target Score Matching (TSM) mitigates this when clean data scores ar…