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Multivariate Representation Learning for Information Retrieval

Multivariate Representation Learning for Information Retrieval

27 April 2023
Hamed Zamani
Michael Bendersky
    DML
ArXivPDFHTML

Papers citing "Multivariate Representation Learning for Information Retrieval"

6 / 6 papers shown
Title
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information
  Retrieval Models
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Nandan Thakur
Nils Reimers
Andreas Rucklé
Abhishek Srivastava
Iryna Gurevych
VLM
231
971
0
17 Apr 2021
Overview of the TREC 2020 deep learning track
Overview of the TREC 2020 deep learning track
Nick Craswell
Bhaskar Mitra
Emine Yilmaz
Daniel Fernando Campos
54
368
0
15 Feb 2021
On the Calibration and Uncertainty of Neural Learning to Rank Models
On the Calibration and Uncertainty of Neural Learning to Rank Models
Gustavo Penha
C. Hauff
171
30
0
12 Jan 2021
RocketQA: An Optimized Training Approach to Dense Passage Retrieval for
  Open-Domain Question Answering
RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering
Yingqi Qu
Yuchen Ding
Jing Liu
Kai Liu
Ruiyang Ren
Xin Zhao
Daxiang Dong
Hua-Hong Wu
Haifeng Wang
RALM
OffRL
214
594
0
16 Oct 2020
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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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