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Exploring Classic and Neural Lexical Translation Models for Information
  Retrieval: Interpretability, Effectiveness, and Efficiency Benefits

Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits

12 February 2021
Leonid Boytsov
Zico Kolter
ArXivPDFHTML

Papers citing "Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency Benefits"

2 / 2 papers shown
Title
Overview of the TREC 2019 deep learning track
Overview of the TREC 2019 deep learning track
Nick Craswell
Bhaskar Mitra
Emine Yilmaz
Daniel Fernando Campos
E. Voorhees
180
465
0
17 Mar 2020
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,746
0
26 Sep 2016
1