Papers by Yunxiang Zhao

2 papers
MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data (2022.acl-long)

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Challenge: Existing benchmarks for numerical reasoning over hybrid data only include a single flat table in each document .
Approach: They propose a new benchmark with QA pairs over multi hierarchical tabular and textual data.
Outcome: The proposed model is more complex and challenging than existing benchmarks and is available on github . it uses facts retrieving to extract relevant facts from both tables and text and symbolic reasoning over retrieved facts.
DaMSTF: Domain Adversarial Learning Enhanced Meta Self-Training for Domain Adaptation (2023.acl-long)

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Challenge: Existing approaches to domain adaptation only use reliable pseudo instances, i.e., pseudo instances with high prediction confidence, to retrain the model.
Approach: They propose a domain adversarial learning enhanced self-training framework that uses meta-learning to estimate the importance of each pseudo instance and a meta constructor to construct the meta-validation set.
Outcome: The proposed framework reduces label noise and preserves hard examples while maintaining accuracy.

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