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Express Language Modeling

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arXiv:2606. 10944v1 Announce Type: cross Abstract: We introduce a new tool, Express, for converting a non-causal attention approximation into a causal approximation with matching approximation guarantees.

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Authors: Albert Gong, Annabelle Michael Carrell, Raaz Dwivedi, Lester Mackey
Released: 2026-06-10 (29d ago)
Topic: Related to current project
Relation to my work: Read next because Express Language Modeling 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, fill, source, line, rate, implement, trained, length. Source: arxiv stat.ML (Machine Learning).
arXiv: 2606.10944

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