{"title":"为大型语言模型构建日语金融基准","authors":"Masanori Hirano","doi":"arxiv-2403.15062","DOIUrl":null,"url":null,"abstract":"With the recent development of large language models (LLMs), models that\nfocus on certain domains and languages have been discussed for their necessity.\nThere is also a growing need for benchmarks to evaluate the performance of\ncurrent LLMs in each domain. Therefore, in this study, we constructed a\nbenchmark comprising multiple tasks specific to the Japanese and financial\ndomains and performed benchmark measurements on some models. Consequently, we\nconfirmed that GPT-4 is currently outstanding, and that the constructed\nbenchmarks function effectively. According to our analysis, our benchmark can\ndifferentiate benchmark scores among models in all performance ranges by\ncombining tasks with different difficulties.","PeriodicalId":501294,"journal":{"name":"arXiv - QuantFin - Computational Finance","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Construction of a Japanese Financial Benchmark for Large Language Models\",\"authors\":\"Masanori Hirano\",\"doi\":\"arxiv-2403.15062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the recent development of large language models (LLMs), models that\\nfocus on certain domains and languages have been discussed for their necessity.\\nThere is also a growing need for benchmarks to evaluate the performance of\\ncurrent LLMs in each domain. Therefore, in this study, we constructed a\\nbenchmark comprising multiple tasks specific to the Japanese and financial\\ndomains and performed benchmark measurements on some models. Consequently, we\\nconfirmed that GPT-4 is currently outstanding, and that the constructed\\nbenchmarks function effectively. According to our analysis, our benchmark can\\ndifferentiate benchmark scores among models in all performance ranges by\\ncombining tasks with different difficulties.\",\"PeriodicalId\":501294,\"journal\":{\"name\":\"arXiv - QuantFin - Computational Finance\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Computational Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2403.15062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Computational Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2403.15062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Construction of a Japanese Financial Benchmark for Large Language Models
With the recent development of large language models (LLMs), models that
focus on certain domains and languages have been discussed for their necessity.
There is also a growing need for benchmarks to evaluate the performance of
current LLMs in each domain. Therefore, in this study, we constructed a
benchmark comprising multiple tasks specific to the Japanese and financial
domains and performed benchmark measurements on some models. Consequently, we
confirmed that GPT-4 is currently outstanding, and that the constructed
benchmarks function effectively. According to our analysis, our benchmark can
differentiate benchmark scores among models in all performance ranges by
combining tasks with different difficulties.