Representation Sparsification with Hybrid Thresholding for Fast SPLADE-based Document Retrieval
Representation Sparsification with Hybrid Thresholding for Fast SPLADE-based Document Retrieval
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DOI:
10.1145/3539618.3592051
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发表时间:
2023-06
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影响因子:
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通讯作者:
Yifan Qiao;Yingrui Yang;Shanxiu He;Tao Yang
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文献类型:
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作者:
Yifan Qiao;Yingrui Yang;Shanxiu He;Tao Yang
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.