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PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking

2022-05-18 04:38:15
Yixuan Qiao, Hao Chen, Yongquan Lai, Jun Wang, Tuozhen Liu, Xianbin Ye, Rui Fang, Peng Gao, Guotong Xie
arXiv_CL
       
Abstract

This paper describes the PASH participation in TREC 2021 Deep Learning Track. In the recall stage, we adopt a scheme combining sparse and dense retrieval method. In the multi-stage ranking phase, point-wise and pair-wise ranking strategies are used one after another based on model continual pre-trained on general knowledge and document-level data. Compared to TREC 2020 Deep Learning Track, we have additionally introduced the generative model T5 to further enhance the performance.

Abstract (translated)

URL

https://arxiv.org/abs/2205.11245

PDF

https://arxiv.org/pdf/2205.11245.pdf

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