Apr 15, 2019 · In this work, we investigate how two pretrained contextualized language models (ELMo and BERT) can be utilized for ad-hoc document ranking.
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In this work, we investigate how two pretrained contextualized language models (ELMo and BERT) can be utilized for ad-hoc document ranking.
In this work, we investigate how two pretrained contextualized language models. (ELMo and BERT) can be utilized for ad-hoc document ranking. Through experiments ...
This work investigates how two pretrained contextualized language models (ELMo and BERT) can be utilized for ad-hoc document ranking and proposes a joint ...
We demonstrate the effectiveness of using BERT classification for document ranking ("Vanilla BERT") and show that BERT embeddings can be used by prior neural ...
Apr 16, 2019 · In this work, we investigate how two pretrained contextualized language modes (ELMo and BERT) can be utilized for ad-hoc document ranking.
The CEDR model achieved SOTA status in 2019, second only to PACRR-DRMM [32] , and its performance is among the best to date [47]. See Figure 3 for an overview ...
Apr 15, 2019 · In this work, we investigate how two pretrained contextualized language modes (ELMo and BERT) can be utilized for ad-hoc document ranking.
Oct 6, 2024 · Sean MacAvaney, Andrew Yates, Arman Cohan , Nazli Goharian: CEDR: Contextualized Embeddings for Document Ranking. SIGIR 2019: 1101-1104.
CEDR: Contextualized Embeddings for Document Ranking We call this joint approach CEDR (Contextualized Embeddings for Document Ranking).