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Prefer to Classify: Improving Text Classifiers via Auxiliary Preference Learning
Jaehyung Kim
, Jinwoo Shin
,
Dongyeop Kang
Computer Science and Engineering
Research output
:
Contribution to journal
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Conference article
›
peer-review
Overview
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Keyphrases
Preference Learning
100%
Text Classifier
100%
Input Text
66%
Model Accuracy
33%
Input-output
33%
Deep Neural Network
33%
Cooperative Effects
33%
Publicly Available
33%
Low Pay
33%
Pairwise Comparison
33%
New Alternatives
33%
Classification Task
33%
Marginal Impact
33%
Training Symbol
33%
Human Cost
33%
Additional Inputs
33%
Crowd Worker
33%
Auxiliary Data
33%
Data Annotation
33%
GPT-3
33%
Large-scale Pre-trained Model
33%
Multi-task Learning Framework
33%
NLP Tasks
33%
NLP Benchmark
33%
Computer Science
Annotation
100%
Preference Learning
100%
Deep Neural Network
33%
Input/Output
33%
Model Accuracy
33%
Multitask Learning
33%
Training Signal
33%
Learning Framework
33%
Generative Pre-Trained Transformer 3
33%
Classification Task
33%
Pairwise Comparison
33%
Large Language Model
33%