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Flow Matching for Efficient and Scalable Data Assimilation

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arXiv:2508. 13313v4 Announce Type: replace Abstract: Data assimilation (DA) estimates a dynamical system's state from noisy observations.

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Authors: Taos Transue, Bohan Chen, So Takao, Bao Wang
Released: 2026-06-19 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Flow Matching for Efficient and Scalable Data Assimilation overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "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: code, class, line, rate, model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2508.13313

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