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arXiv · 2306.11293

Representation Sparsification with Hybrid Thresholding for Fast SPLADE-based Document Retrieval

Yifan Qiao·Yingrui Yang·Shanxiu He·Tao Yang
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Abstract

Learned sparse document representations using a transformer-based neural model has been found to be attractive in both relevance effectiveness and time efficiency. This paper describes a representation sparsification scheme based on hard and soft thresholding with an inverted index approximation for faster SPLADE-based document retrieval. It provides analytical and experimental results on the impact of this learnable hybrid thresholding scheme.

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Yifan Qiao, Yingrui Yang, Shanxiu He, Tao Yang. 2023-06-20. Representation Sparsification with Hybrid Thresholding for Fast SPLADE-based Document Retrieval. https://doi.org/10.1145/3539618.3592051

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