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The ComOM shared task aims to extract comparative opinions from productreviews in Vietnamese language. There are two sub-tasks, including (1)Comparative Sentence Identification (CSI) and (2) Comparative ElementExtraction (CEE). The first task is to identify whether the input is acomparative review, and the purpose of the second task is to extract thequintuplets mentioned in the comparative review. To address this task, our teamproposes a two-stage system based on fine-tuning a BERTology model for the CSItask and unified multi-task instruction tuning for the CEE task. Besides, weapply the simple data augmentation technique to increase the size of thedataset for training our model in the second stage. Experimental results showthat our approach outperforms the other competitors and has achieved the topscore on the official private test.

ComOM at VLSP 2023: A Dual-Stage Framework with BERTology and Unified Multi-Task Instruction Tuning Model for Vietnamese Comparative Opinion Mining