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Uncertainty-Aware Label Refinement for Sequence Labeling

Uncertainty-Aware Label Refinement for Sequence Labeling

19 December 2020
Tao Gui
Jiacheng Ye
Qi Zhang
Zhengyan Li
Zichu Fei
Yeyun Gong
Xuanjing Huang
    BDL
ArXivPDFHTML

Papers citing "Uncertainty-Aware Label Refinement for Sequence Labeling"

7 / 7 papers shown
Title
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive
  Learning
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning
Sheng Zhang
Hao Cheng
Jianfeng Gao
Hoifung Poon
33
47
0
30 Aug 2022
Improving Graph-based Sentence Ordering with Iteratively Predicted
  Pairwise Orderings
Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
Shaopeng Lai
Ante Wang
Fandong Meng
Jie Zhou
Yubin Ge
Jiali Zeng
Junfeng Yao
Degen Huang
Jinsong Su
25
8
0
13 Oct 2021
LightNER: A Lightweight Tuning Paradigm for Low-resource NER via
  Pluggable Prompting
LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting
Xiang Chen
Lei Li
Shumin Deng
Chuanqi Tan
Changliang Xu
Fei Huang
Luo Si
Huajun Chen
Ningyu Zhang
VLM
34
65
0
31 Aug 2021
NCRF++: An Open-source Neural Sequence Labeling Toolkit
NCRF++: An Open-source Neural Sequence Labeling Toolkit
Jie Yang
Yue Zhang
58
188
0
14 Jun 2018
Design Challenges and Misconceptions in Neural Sequence Labeling
Design Challenges and Misconceptions in Neural Sequence Labeling
Jie Yang
Shuailong Liang
Yue Zhang
118
161
0
12 Jun 2018
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
197
745
0
06 Jun 2015
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
9,145
0
06 Jun 2015
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