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To improve the performance of the dual-encoder retriever, one effective approach is knowledge distillation from the cross-encoder ranker.
Document expansion by query prediction
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho. 2019b · 1904
Earlier work this paper cites.
Augmenting data with mixup for sentence classification: An empirical study
Hongyu Guo, Yongyi Mao, and Richong Zhang. 2019 · 1905
Earlier work this paper cites.
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Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Context-aware sentence/passage term importance estimation for first stage retrieval
Zhuyun Dai and Jamie Callan. 2019a · 1910
Earlier work this paper cites.
Curriculum learning for dense retrieval distillation
Hansi Zeng, Hamed Zamani, and Vishwa Vinay. 2022 · 1983
Earlier work this paper cites.
Overview of the TREC 2019 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees. 2020 · 2003
Earlier work this paper cites.
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Earlier work this paper cites.
The probabilistic relevance framework: BM25 and beyond
Stephen E. Robertson and Hugo Zaragoza. 2009 · 2009
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean. 2015 · 2015
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Matthew L. Henderson, Rami Al-Rfou, Brian Strope, Yun-Hsuan Sung, László Lukács, Ruiqi Guo, Sanjiv Kumar, Balint Miklos, and Ray Kurzweil. 2017 · 2017
Earlier work this paper cites.
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Earlier work this paper cites.
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Wizard of wikipedia: Knowledge-powered conversational agents
Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2018 · 2018
Earlier work this paper cites.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Later among the works it cites.
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Colbertv2: Effective and efficient retrieval via lightweight late interaction
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