# Advancements and Challenges in Bangla Question Answering Models: A Comprehensive Review

Source: [Advancements and Challenges in Bangla Question Answering Models: A Comprehensive Review](<https://www.sota2.com/research/paper/68fa763e1e209131cea6c120>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T03:50:30.323Z

Authors: Md Iftekhar Islam Tashik, Abdullah Khondoker, Enam Ahmed Taufik, Antara Firoz Parsa, S M Ishtiak Mahmud

Published: 2024-12-16T14:42:26.000Z

## Abstract

The domain of Natural Language Processing (NLP) has experienced notable progress in the evolution of Bangla Question Answering (QA) systems. This paper presents a comprehensive review of seven research articles that contribute to the progress in this domain. These research studies explore different aspects of creating question-answering systems for the Bangla language. They cover areas like collecting data, preparing it for analysis, designing models, conducting experiments, and interpreting results. The papers introduce innovative methods like using LSTM-based models with attention mechanisms, context-based QA systems, and deep learning techniques based on prior knowledge. However, despite the progress made, several challenges remain, including the lack of well-annotated data, the absence of high-quality reading comprehension datasets, and difficulties in understanding the meaning of words in context. Bangla QA models' precision and applicability are constrained by these challenges. This review emphasizes the significance of these research contributions by highlighting the developments achieved in creating Bangla QA systems as well as the ongoing effort required to get past roadblocks and improve the performance of these systems for actual language comprehension tasks.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2412.11823>)

[PDF](<https://arxiv.org/pdf/2412.11823.pdf>)