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Neural Machine Translation for Low-Resource Tangkhul--English

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arXiv:2606. 25365v1 Announce Type: new Abstract: We present a study on low-resource machine translation for the Tangkhul-English (nmf-en) language pair.

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Authors: Chormi Zimik Vashai, Agniva Maiti
Released: 2026-06-25 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Neural Machine Translation for Low-Resource Tangkhul--English 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, latin, under, source, test, language. Source: arxiv cs.CL (NLP).
arXiv: 2606.25365

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