[3M5-OS-12b] OS-12

[3M5-OS-12b-02] Term Selection for Stock Price Fluctuation Images by Large Mulitmodal Models

〇Shunsuke NIshida¹, Takehito Utsuro¹ (1. University of Tsukuba)

Keywords:stock price fluctuation, stock term selection, large language models, GPT-4V, multimodal

In stock price fluctuation articles, stock terms are frequently used to
describe stock price fluctuations. In order to automatically generate
such articles, we evaluated a method for automatically selecting terms
that appropriately represent the characteristics of stock price
fluctuations by feeding a chart of stock price fluctuations over several
days to large multimodal models. The method was found to be able to
select, with high accuracy, terms that are manually assigned by
journalists to articles on stock price fluctuations and terms that are
close to those assigned by journalists. Comparative evaluation results
also show that large multimodal models perform slightly worse but still
mostly well compared with large language models such as GPT-4 (zero-shot
and few-shot) and GPT-3.5 (fine-tuning).