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Rethinking Noisy Label Learning in Real-world Annotation Scenarios from
  the Noise-type Perspective

Rethinking Noisy Label Learning in Real-world Annotation Scenarios from the Noise-type Perspective

28 July 2023
Renyu Zhu
Haoyu Liu
Runze Wu
Min-Hsien Lin
Tangjie Lv
Changjie Fan
Haobo Wang
    NoLa
ArXivPDFHTML

Papers citing "Rethinking Noisy Label Learning in Real-world Annotation Scenarios from the Noise-type Perspective"

2 / 2 papers shown
Title
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
303
11,881
0
04 Mar 2022
Curriculum Loss: Robust Learning and Generalization against Label
  Corruption
Curriculum Loss: Robust Learning and Generalization against Label Corruption
Yueming Lyu
Ivor W. Tsang
NoLa
47
172
0
24 May 2019
1