47 citations · 153 across the 19 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.IR2020★ 6 cited
Simplified TinyBERT: Knowledge Distillation for Document Retrieval
Xuanang Chen, Ben He, Kai Hui +2
Despite the effectiveness of utilizing the BERT model for document ranking, the high computational cost of such approaches limits their uses. To this end, this paper first empirica…
cs.IR2020★ 4 cited
BERT-QE: Contextualized Query Expansion for Document Re-ranking
Zhi Zheng, Kai Hui, Ben He +3
Query expansion aims to mitigate the mismatch between the language used in a query and in a document. However, query expansion methods can suffer from introducing non-relevant info…
cs.IR2020★ 44 cited
PARADE: Passage Representation Aggregation for Document Reranking
Canjia Li, Andrew Yates, Sean MacAvaney +2
Pretrained transformer models, such as BERT and T5, have shown to be highly effective at ad-hoc passage and document ranking. Due to inherent sequence length limits of these models…