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Transfer learning for causal forest

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arXiv:2606. 07693v1 Announce Type: new Abstract: Transfer learning addresses the challenge of transfering knowledge from one domain to another.

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Authors: B\'er\'enice-Alexia Jocteur (ICJ, PSPM), V\'eronique Maume-Deschamps (ICJ, PSPM), Pierre Ribereau (PSPM, ICJ)
Released: 2026-06-09 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Transfer learning for causal forest 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: text, good, source, trained, another, model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2606.07693

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