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Latent Process Generator Matching

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arXiv:2605. 20547v1 Announce Type: cross Abstract: Many recent flow-matching and diffusion-style generative models rely on auxiliary stochastic dynamics during training: a richer process is simulated to define conditional targets, but the auxiliary state is either intractable to sample at generation time or simply not part of the desired output.

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Authors: Lukas Billera, Hedwig Nora Nordlinder, Ben Murrell
Released: 2026-05-21 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Latent Process Generator Matching overlaps with experiment "Implement Chen et al. persona-vector extraction recipe and compare to project's centroid-difference recipe", experiment "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: project, model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2605.20547

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