@InProceedings{huidrom-EtAl:2026:wmt2,
  author    = {Huidrom, Rudali  and  Kumar, Vikas  and  Pangsatabam, Hoomexsun  and  Das, Pinaki  and  Khanganba, K. Kabi  and  Zeno, Nongmaithem  and  KHUMUKCHAM, NICHOLAS  and  Okram, Mangalton  and  Konjengbam, Justice  and  Jamalpoor, Sai Varun  and  Khangembam, Alex D. Nelson  and  Konjengbam, Anand  and  Goyal, Vikram},
  title     = {PANINI: Improving Low-Resource English-Manipuri Translation in Two Scripts via rsLoRA and Three-Stream Self-Augmentation},
  booktitle      = {Proceedings of the Eleventh Conference on Machine Translation},
  month          = {October},
  year           = {2026},
  address        = {Budapest, Hungary},
  publisher      = {Association for Computational Linguistics},
  pages     = {2161--2169},
  abstract  = {We describe team PANINI's submission to the WMT 2026 Shared Task on Low-Resource Indic Language Translation. We submit primary systems for English↔Manipuri (Meiteilon) in both the Bengali (mni Beng) and Meitei Mayek (mni Mtei) scripts, covering all four directions. Rather than one shared multilingual adapter, we train four independent rank-stabilized LoRA (rsLoRA) adapters over IndicTrans2-1B, one per direction. Each adapter is trained on the authentic bitext plus three filtered synthetic streams the model generates for itself: back-translation, forward translation, and iterative pseudo-labelling, with subword regularisation and a script-aware processing pipeline. Our system obtains a COMET score of 92.31 and a BERTScore of 98.85 on English↔Manipuri (Meitei Mayek), the best in the direction. On the into-English directions, it reaches a COMET of 82.90 for mni Beng↔en and 80.20 for mniMtei↔en. These results show that per-direction adapters combined with self-generated synthetic data are effective even when authentic bitext is limited to a few thousand sentence pairs, and that a script-aware processing pipeline is necessary to produce well-formed output in both Manipuri scripts. The code and resources are released on GitHub.},
  url       = {https://aclanthology.org/2026.wmt-1.154}
}