论文标题
repbert：第一阶段检索的上下文化文本嵌入
RepBERT: Contextualized Text Embeddings for First-Stage Retrieval
论文作者
论文摘要
尽管查询和文档之间的确切术语匹配是执行第一阶段检索的主要方法，但我们提出了一种称为repbert的方法，以表示具有固定长度上下文化嵌入的文档和查询。查询和文档嵌入的内部产品被视为相关得分。在MS MARCO通过排名任务上，Repbert在所有初始检索技术中都取得了最新的结果。它的效率与词袋方法相媲美。
Although exact term match between queries and documents is the dominant method to perform first-stage retrieval, we propose a different approach, called RepBERT, to represent documents and queries with fixed-length contextualized embeddings. The inner products of query and document embeddings are regarded as relevance scores. On MS MARCO Passage Ranking task, RepBERT achieves state-of-the-art results among all initial retrieval techniques. And its efficiency is comparable to bag-of-words methods.
