Santham : A Curated Sanskrit–Tamil Dataset with Anvaya and Segmentation for Building and Evaluating Machine Translation

MythoBERT 1.0: A pre-trained language model for Hindu mythology

Aligned Parallel Corpus of the Vedic Saṁhitās for Machine Translation

Dataset Curation for Kalabari NMT System

A transferable curation framework for endangered languages, the first sizable Kalabari-English parallel corpus, and baseline experiments that reveal both the promise and the hallucination pitfalls of training on highly constrained, domain-specific data are contributed.

Systematic Analysis of Large Language Models and Transformer-Based Machine Translation for English-Tamil and Tamil-English Across Diverse Datasets

The findings show that the quality of the datasets and their alignment with the domain will greatly affect the performance of the model, that attention-based mechanisms can aid in explain ability, and that few-shot large language models can still produce structurally coherent translations of Tamil.

Padamitra: Grounded Glossary Generation for Classical Sanskrit

We introduce grounded glossary generation, a structured task requiring models to recover semantically meaningful Sanskrit phrases and produce translation-grounded meanings from a sloka-translation pair, formalizing the traditional patha commentary practice as an evaluable NLP objective. We construct a benchmark of 31,3...

Low-Resource Machine Translation of Yoruba Text to Nigerian Pidgin Using NLLB-200 and Parameter-Efficient Fine-Tuning

Machine translation for low-resource and structurally divergent languages remains a significant challenge, particularly when mapping highly tonal languages to contact languages with fluid orthographies. This study presents the development of a translation system for Yoruba to Nigerian Pidgin, which addresses a critical...