AINeutralarXiv – CS AI · 18h ago6/10
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Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan
Researchers developed a data synthesis methodology for neural machine translation of Q'eqchi' Mayan, using synthetic corpora derived from community dictionaries and Parameter-Efficient Fine-Tuning to avoid extractive web-scraping. While the approach achieved strong structural performance (BLEU 42.02 on synthetic data), it revealed a critical gap: the model excels at learning grammar but fails to acquire authentic semantic grounding (BLEU 0.59 on organic text), suggesting synthetic bootstrapping alone cannot replace real-world linguistic diversity.