Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling-Reference-Cited by-同舟云学术

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Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Published:2021-07-11 Issue: Volume: Page:
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Container-title:Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Hofstätter Sebastian¹,Lin Sheng-Chieh²,Yang Jheng-Hong²,Lin Jimmy²,Hanbury Allan¹

Affiliation:

1. TU Wien, Vienna, Austria

2. University of Waterloo, Waterloo, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3404835.3462891

Reference45 articles.

1. Learning to rank

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4. Neural Passage Quality Estimation for Static Pruning;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

5. EASE-DR: Enhanced Sentence Embeddings for Dense Retrieval;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

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