Typo-Robust Sentence Representation Learning for Dense Retrieval

Anonymous

Keywords: dense retrieval, sentence representation learning, handling misspellings

Abstract: Dense retrieval is a basic building block of information retrieval applications. One of the main challenges of dense retrieval in real-world settings is the handling of queries containing misspelled words. A popular approach to handling misspelled queries is minimizing the representations discrepancy between misspelled queries and their pristine ones. Unlike the existing approaches which only focus on the alignment between misspelled and pristine queries, our method also improves the contrast between each misspelled query and its surrounding queries. To assess the effectiveness of our proposed method, we compare it against the existing competitors using two benchmark datasets and two base encoders. Our method outperforms the competitors in all cases with misspelled queries.

Paper Type: short

Research Area: Information Retrieval and Text Mining