BanglaMamba: Exploring State Space Models for Bangla Fake News Detection
Fake news detection has become an important Natural Language Processing (NLP) task due to the rapid spread of misinformation through online news platforms and social media. While transformer-based models such as BanglaBERT achieve strong performance for Bangla text classification, their quadratic computational complexity makes them less suitable for long-document processing in resource-constrained environments. This paper investigates Mamba-based State Space Models (SSMs) as an efficient alternative for Bangla fake news detection. We propose BanglaMamba and compare it with pre-trained BanglaBERT and a similarly configured BERT model trained from scratch. Experimental results show that Ban...
| Authors | M. K. Khalidi Siam |
|---|---|
| Primary category | cs.CL |
| Published | 25 August 2026 |
| Last updated at source | 25 August 2026 |
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