Author

Farig Sadeque

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Preprint Aug 2026

BengaliMCQ: Automatic Generation and Answer Prediction of Academic Multiple-Choice Questions in a Low-Resource Language

A structure-aware RAG framework is proposed that models Bengali textbooks as hierarchical graphs and uses a contrastively trained graph neural network to retrieve a small set of relevant passages, enabling topic-specific multiple-choice question (MCQ) generation and in-domain answer prediction.

Abu Tarabin Surzo, A. K. M. Nihalul Kabir, Sm Azmain Faysal et al. · 0 citations

Jul 2026

When Does Knowledge Distillation Hurt? Reliability-Aware Distillation for Low-Resource Language Summarization

The stronger method is evaluated across 15 typologically diverse XL-Sum languages organised into three sets, beating the CE-only baseline on 10/15 languages; gains are most reliable where the two teachers contribute complementary signal, and weakest where they have saturated or jointly weak target-language coverage.

Dipto Sumit, Ankan Kumar Roy Srizon, Sadia Khair Rodela et al. · arXiv.org · 0 citations

#natural language process... Preprint Aug 2026

Below the Noise Floor: Bimodal Seed Collapse and Distinct Failure Modes in Small-Model Knowledge Distillation

On a 740-instance healthcare API routing task with a 1.5B Qwen student and a 20B teacher, eight KD variants are compared against supervised cross-entropy, finding single-seed evaluation is unable to detect central failure modes in small-model KD.

Dipto Sumit, Sakib Ul Haque, Farig Sadeque · 0 citations