Papers by Hanxuan Yang

2 papers
Cross-Lingual Cross-Target Stance Detection with Dual Knowledge Distillation Framework (2023.emnlp-main)

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Challenge: Existing studies on stance detection were conducted mainly in English due to the low-resource problem in most non-English languages.
Approach: They propose to use a cross-lingual teacher and a teacher to transfer knowledge from source to target language to bridge the discrepancy between languages.
Outcome: The proposed framework bridges the discrepancy between languages and generalizes the knowledge to unseen targets in target language.
Target-Oriented Relation Alignment for Cross-Lingual Stance Detection (2023.findings-acl)

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Challenge: Existing work on cross-lingual stance detection has ignored the inconsistency in the occurrences and distributions of targets between languages, which consequently degrades the performance of stance detector in low-resource languages.
Approach: They propose a fine-grained method which considers both target-level associations and language-level alignments to learn the in-language and cross-language associations.
Outcome: The proposed method is compared with competing methods under variant settings and shows that it performs better in low-resource languages.

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