Evaluation Results of UTUtLB25 Team in NTCIR-18 U4 Task of Table Question Answering of Securities Reports

The goal of this paper is to develop a system for participating in the information extraction task from tables in securities reports (NTCIR- 18 U4 Task). The NTCIR-18 U4 Task consists of two distinct tasks: (1) retrieving the table that contains the relevant data. (2) extracting the desired data from the table to address the question. For the first task, we will utilize a pre-trained model that has demonstrated strong performance in table retrieval, and we will fine-tune the model to enhance its effectiveness for this specific task. In the second task, We will employ the latest Large Language Models (LLMs), which have shown excellent results across a variety of Natural Language Processing tasks. This approach is expected to achieve state-ofthe- art performance, surpassing existing pre-trained BERT-based models.