Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations
Jimmy Lin(University of Maryland, College Park), Rodrigo Nogueira(United Food and Commercial Workers), Jheng-Hong Yang(University of Waterloo), Xueguang Ma(University of Waterloo), Sheng-Chieh Lin(University of Waterloo), Ronak Pradeep
Cited by 31
Related Papers
BERTimbau: Pretrained BERT Models for Brazilian Portuguese
|Lecture notes in computer science|2020|611
Document Ranking with a Pretrained Sequence-to-Sequence Model
|Unknown|2020|434
Fingerprint Liveness Detection Using Convolutional Neural Networks
|IEEE Transactions on Information Forensics and Security|2016|357
Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations
|Unknown|2021|355
Passage Re-ranking with BERT
|arXiv (Cornell University)|2019|346