PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking
Yixuan Qiao
Hao Chen
Jun Wang
Yongquan Lai
Tuozhen Liu
Xianbin Ye
Xin Tang
Rui Fang
Peng Gao
Wenfeng Xie
Guotong Xie

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.
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