论文标题
CX DB8：可查询的提取摘要和语义搜索引擎
CX DB8: A queryable extractive summarizer and semantic search engine
论文作者
论文摘要
竞争性辩论越来越多的技术性使竞争对手在寻找加速证据生产的工具。我们发现，竞争性辩论者执行的独特类型的提取性摘要 - 对特定目标含义有偏见的摘要 - 可以使用无监督的预先训练的文本矢量化模型中的最新创新进行执行。我们介绍了CX_DB8，这是一种可查询的单词级提取性摘要和证据创建框架，可以快速，有偏见的摘要对仲裁大小的文本。 CX_DB8嵌入框架的使用情况意味着，随着基础模型的改善，CX_DB8也将有所改善。我们观察到CX_DB8还可以用作语义搜索引擎，并将应用程序作为程序和网页中传统“查找”功能的补充。 CX_DB8目前由竞争性辩论者使用，可通过https://github.com/hellisotherpeople/cx_db8向公众使用
Competitive Debate's increasingly technical nature has left competitors looking for tools to accelerate evidence production. We find that the unique type of extractive summarization performed by competitive debaters - summarization with a bias towards a particular target meaning - can be performed using the latest innovations in unsupervised pre-trained text vectorization models. We introduce CX_DB8, a queryable word-level extractive summarizer and evidence creation framework, which allows for rapid, biasable summarization of arbitarily sized texts. CX_DB8s usage of the embedding framework Flair means that as the underlying models improve, CX_DB8 will also improve. We observe that CX_DB8 also functions as a semantic search engine, and has application as a supplement to traditional "find" functionality in programs and webpages. CX_DB8 is currently used by competitive debaters and is made available to the public at https://github.com/Hellisotherpeople/CX_DB8
