Papers by Yanxian Huang

1 papers
Exploring Representation-level Augmentation for Code Search (2022.emnlp-main)

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Challenge: Recent data augmentations for code search are at the raw-data level, which requires additional code analysis and training cost.
Approach: They propose a general format of representation-level augmentation that unifies existing methods.
Outcome: The proposed methods can boost the performance of code search models on a large-scale dataset.

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