CEDR: Contextualized Embeddings for Document Ranking

15 Apr 2019Sean MacAvaneyAndrew YatesArman CohanNazli Goharian

Although considerable attention has been given to neural ranking architectures recently, far less attention has been paid to the term representations that are used as input to these models. In this work, we investigate how two pretrained contextualized language models (ELMo and BERT) can be utilized for ad-hoc document ranking... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Ad-Hoc Information Retrieval TREC Robust04 CEDR-KNRM [email protected] 0.4667 # 1
[email protected] 0.5381 # 1
Ad-Hoc Information Retrieval TREC Robust04 Vanilla BERT [email protected] 0.4042 # 4
[email protected] 0.4541 # 5