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Are Data Augmentation Methods in Named Entity Recognition Applicable for
  Uncertainty Estimation?

Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation?

2 July 2024
Wataru Hashimoto
Hidetaka Kamigaito
Taro Watanabe
ArXivPDFHTML

Papers citing "Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation?"

6 / 6 papers shown
Title
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks
Wataru Hashimoto
Hidetaka Kamigaito
Taro Watanabe
52
0
0
02 Jul 2024
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the
  Impact of Method & Data Scarcity
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
Dennis Ulmer
J. Frellsen
Christian Hardmeier
179
22
0
20 Oct 2022
Re-Examining Calibration: The Case of Question Answering
Re-Examining Calibration: The Case of Question Answering
Chenglei Si
Chen Zhao
Sewon Min
Jordan L. Boyd-Graber
56
30
0
25 May 2022
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
243
289
0
17 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,652
0
05 Dec 2016
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
247
9,109
0
06 Jun 2015
1