ReNeuIR: Reaching Efficiency in Neural Information Retrieval-Reference-Cited by-同舟云学术

ReNeuIR: Reaching Efficiency in Neural Information Retrieval

Published:2022-07-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Bruch Sebastian¹,Lucchese Claudio²,Nardini Franco Maria³

Affiliation:

1. Pinecone, New York, NY, USA

2. Ca' Foscary University of Venice, Venice, Italy

3. ISTI-CNR, Pisa, Italy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477495.3531704

Reference47 articles.

1. Nima Asadi . 2013. Multi-Stage Search Architectures for Streaming Documents . University of Maryland. Nima Asadi. 2013. Multi-Stage Search Architectures for Streaming Documents. University of Maryland.

2. Fast candidate generation for two-phase document ranking

3. Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures

4. Fast candidate generation for real-time tweet search with bloom filter chains

5. Training Efficient Tree-Based Models for Document Ranking

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