Papers by Aoying Zhou

2 papers
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification (2021.findings-acl)

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Challenge: Existing approaches for few-shot text classification rely on exploitation of lexical features and distributional signatures on training data, while neglecting to strengthen the model's ability to adapt to new tasks.
Approach: They propose a meta-learning framework integrated with an adversarial domain adaptation network to improve the model's adaptive ability and generate high-quality text embedding for new classes.
Outcome: The proposed framework outperforms the state-of-the-art models on four datasets and shows clear superiority over existing models.
SphereRE: Distinguishing Lexical Relations with Hyperspherical Relation Embeddings (P19-1)

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Challenge: Lexical relations are relations between terms in lexicons.
Approach: They propose a neural representation learning model to distinguish lexical relations among term pairs based on hyperspherical relation embeddings.
Outcome: The proposed model outperforms state-of-the-art models on several benchmarks.

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