Papers by Ming Pang

1 papers
A Semi-supervised Scalable Unified Framework for E-commerce Query Classification (2025.acl-industry)

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Challenge: Existing query classification methods rely on posterior click behavior to construct training samples, resulting in insufficient prior information for modeling.
Approach: They propose a semi-supervised scaleable unified framework that integrates enhanced modules to unify query classification tasks.
Outcome: The proposed framework outperforms the state-of-the-art models in offline and online A/B experiments.

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