Team YTY at SemEval 2026 task 12: Option-Aware Retrieval and Cross-Encoder Reasoning Framework for Abductive Event Reasoning

AbstractWe describe a unified system for SemEval-2026 Task 9 on multilingual polarization detection. The task requires binary polarization detection, multi-label target type classification, and multi-label manifestation identification across languages and events with severe class imbalance. Our approach combines (i) targeted data augmentation for low-frequency labels, (ii) merged multitask fine-tuning of Subtask 2 and Subtask 3, and (iii) model fusion to improve cross-lingual stability. Subtask 1 predictions are derived via calibrated inference from the multi-label head. On the development set, multitask training consistently out-performs single-task variants, and fusion yields additional gains, especially for rare labels. We also report ablations and error analyses, highlighting remaining challenges such as implicit polarization and partial-label uncertainty.