<p>Training summary of the applied models.</p>

Flan-T5 and mT5 LLMs were trained on the XLSUM Bengali dataset for text summarization, and they were trained on source domains and fine-tuned on the target domains for domain adaptation. In general-domain summarization on the XLSum Bengali dataset, mT5 achieved stronger overall performance than Flan-T5, with ROUGE-1 and BERTScore values of 0.21 and 0.72, respectively.

The Flan-T5-XLSUM model outperformed other LLMs, achieving a ROUGE score of 0.79, a BLEU score of 0.13 and a BERTScore of 0.86. A human evaluation involving 28 participants was conducted to assess summary fluency, adequacy, and factual consistency across domains, confirming the qualitative effectiveness of the proposed models. A custom dataset is developed with manually annotated categories for domain adaptation purposes, contributing to domain-specific Bengali data.