transformer_1376 at SemEval-2026 Task 9: A Multi-Stage Pipeline with Calibrated Ensembles and Lexical Post-Processing for Online Polarization Detection in Bengali

AbstractThe POLAR @ SemEval-2026 Task 9 deals with the detection of online polarization in a variety of multilingual and multicultural environments. Our team participated in Subtask 1 of the POLAR @ SemEval-2026 Task 9, which mainly deals with binary classification of textual sequences for the detection of polarized stances. In this paper, we proposed a strong classification system for Bengali language based on fine-tuning the BanglaBERT Large model. The methodology used here involves a stratified five-fold cross-validation approach along with a performance-weighted ensemble method, combined with temperature scaling probability calibration and a set of lexical post-processing rules.