Papers by Xianxin Chen

1 papers
Learning to Detect Noisy Labels Using Model-Based Features (2022.findings-emnlp)

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Challenge: Existing approaches to reduce label noise rely on heuristics and sample losses.
Approach: They propose a method that transfers the noise distribution to a clean set and trains a model to distinguish noisy labels from clean ones using model-based features.
Outcome: Empirically, the proposed approach improves over strong baselines on a wide range of tasks including text classification and speech recognition.

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