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arXiv · 2205.11245

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

Yixuan Qiao·Shanshan Zhao·Jun Wang·Hao Chen·Tuozhen Liu·Xianbin Ye·Xin Tang·Rui Fang·Peng Gao·Wenfeng Xie·Guotong Xie
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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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Yixuan Qiao, Shanshan Zhao, Jun Wang, Hao Chen, Tuozhen Liu, Xianbin Ye, Xin Tang, Rui Fang, Peng Gao, Wenfeng Xie, Guotong Xie. 2022-05-18. PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking. https://arxiv.org/abs/2205.11245

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