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Label Error Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Identify labeling errors in data
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond
LEMoN: Label Error Detection using Multimodal Neighbors
Improving Label Error Detection and Elimination with Uncertainty Quantification
AQuA: A Benchmarking Tool for Label Quality Assessment
Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite
Identifying Label Errors in Object Detection Datasets by Loss Inspection
The Re-Label Method For Data-Centric Machine Learning
Identifying Incorrect Annotations in Multi-Label Classification Data
CTRL: Clustering Training Losses for Label Error Detection
Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification
WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.