Papers by Nicholas Botzer

1 papers
TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification (2023.findings-emnlp)

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Challenge: Semi-supervised methods for detecting intent generate a large amount of unlabeled data . labeling data requires substantial human effort, and picking an imbalanced set of examples could lead to poor labels.
Approach: They propose a balanced distance-based pseudo-labeling approach for semisupervised intent classification . they use a ranking-based approach to select samples with a model prediction confidence .
Outcome: The proposed method outperforms existing models on popular datasets.

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