{"title":"OpenMatch-v2:一个一体化的多模态基于plm的信息检索工具包","authors":"Shi Yu, Zhenghao Liu, Chenyan Xiong, Zhiyuan Liu","doi":"10.1145/3539618.3591813","DOIUrl":null,"url":null,"abstract":"Pre-trained language models (PLMs) have emerged as the foundation of the most advanced Information Retrieval (IR) models. Powered by PLMs, the latest IR research has proposed novel models, new domain adaptation algorithms as well as enlarged datasets. In this paper, we present a Python-based IR toolkit OpenMatch-v2. As a full upgrade of OpenMatch proposed in 2021, OpenMatch-v2 incorporates the most recent advancements of PLM-based IR research, providing support for new, cross-modality models and enhanced domain adaptation techniques with a streamlined, optimized infrastructure. The code of OpenMatch is publicly available at https://github.com/OpenMatch/OpenMatch.","PeriodicalId":425056,"journal":{"name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"OpenMatch-v2: An All-in-one Multi-Modality PLM-based Information Retrieval Toolkit\",\"authors\":\"Shi Yu, Zhenghao Liu, Chenyan Xiong, Zhiyuan Liu\",\"doi\":\"10.1145/3539618.3591813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pre-trained language models (PLMs) have emerged as the foundation of the most advanced Information Retrieval (IR) models. Powered by PLMs, the latest IR research has proposed novel models, new domain adaptation algorithms as well as enlarged datasets. In this paper, we present a Python-based IR toolkit OpenMatch-v2. As a full upgrade of OpenMatch proposed in 2021, OpenMatch-v2 incorporates the most recent advancements of PLM-based IR research, providing support for new, cross-modality models and enhanced domain adaptation techniques with a streamlined, optimized infrastructure. The code of OpenMatch is publicly available at https://github.com/OpenMatch/OpenMatch.\",\"PeriodicalId\":425056,\"journal\":{\"name\":\"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval\",\"volume\":\"2016 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3539618.3591813\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3539618.3591813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OpenMatch-v2: An All-in-one Multi-Modality PLM-based Information Retrieval Toolkit
Pre-trained language models (PLMs) have emerged as the foundation of the most advanced Information Retrieval (IR) models. Powered by PLMs, the latest IR research has proposed novel models, new domain adaptation algorithms as well as enlarged datasets. In this paper, we present a Python-based IR toolkit OpenMatch-v2. As a full upgrade of OpenMatch proposed in 2021, OpenMatch-v2 incorporates the most recent advancements of PLM-based IR research, providing support for new, cross-modality models and enhanced domain adaptation techniques with a streamlined, optimized infrastructure. The code of OpenMatch is publicly available at https://github.com/OpenMatch/OpenMatch.