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

Qiao, Yixuan, Chen, Hao, Wang, Jun, Lai, Yongquan, Liu, Tuozhen, Ye, Xianbin, Tang, Xin, Fang, Rui, Gao, Peng, Xie, Wenfeng, Xie, Guotong

arXiv.org Artificial Intelligence 

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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