@inproceedings{oinam-saharia-2025-delab,
    title = "{DELAB}-{IIITM} {WMT}25: Enhancing Low-Resource Machine Translation for {M}anipuri and {A}ssamese",
    author = "Oinam, Dingku  and
      Saharia, Navanath",
    editor = "Haddow, Barry  and
      Kocmi, Tom  and
      Koehn, Philipp  and
      Monz, Christof",
    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.wmt-1.98/",
    doi = "10.18653/v1/2025.wmt-1.98",
    pages = "1222--1226",
    ISBN = "979-8-89176-341-8",
    abstract = "This paper describe DELAB-IIITM{'}s submission system for the WMT25 machine translation shared task. We participated in two sub-task of the Indic Translation Task, en{\ensuremath{\leftrightarrow}}as and en{\ensuremath{\leftrightarrow}}mn i.e. Assamese (Indo Aryan language) and Manipuri (Tibeto Burman language) with a total of six translation directions, including mn{\textrightarrow}en, mn{\textleftarrow}en, en{\textrightarrow}as, en{\textleftarrow}as, mn{\textrightarrow}as, mn{\textleftarrow}as. Our fine tuning process aims to leverages the pretrained multilingual NLLB-200 model, a machine translation model developed by Meta AI as part of the No Language Left Behind (NLLB) project, through two main development, Synthetic parallel corpus creation and Strategic Fine-tuning. The Fine-tuning process involves strict data cleaning protocols, Adafactor optimizer with low learning rate(2e-5), 2 training epochs, train-test data splits to prevent overfitting, and Seq2SeqTrainer framework. The official test data was used to generate the target language with our fine-tuned model. Experimental results show that our method improves the BLEU scores for translation of these two language pairs. These findings confirm that back-translation remains challenging, largely due to morphological complexity and limited data availability."
}