Papers by Ching-Yun Chang

3 papers
Cross-lingual Alignment Methods for Multilingual BERT: A Comparative Study (2020.findings-emnlp)

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Challenge: Multilingual BERT (mBERT) has shown reasonable capability for zero-shot cross-lingual transfer when fine-tuned on downstream tasks.
Approach: They propose to use parallel corpora and rotational alignment methods to improve transfer performance in a zero-shot setting.
Outcome: The proposed method improves rotation-based alignment on Name Entity Recognition and Semantic Slot Filling tasks.
Translation-Enhanced Multilingual Text-to-Image Generation (2023.acl-long)

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Challenge: Existing models for text-to-image generation are mostly based on the English language due to the lack of annotated image-caption data in other languages.
Approach: They propose to use a multilingual multi-modal encoder to bootstrap mTTI systems that can be translated into other languages.
Outcome: The proposed approach mitigates the language gap and improves on standard mTTI datasets.
Learning Target-Specific Representations of Financial News Documents For Cumulative Abnormal Return Prediction (C18-1)

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Challenge: Recent work considers learning dense representations for news titles and abstracts . text representations can address the sparsity of discrete indicators in statistical models .
Approach: They propose to use news abstracts to combine the most informative sentences in news content to learn dense representations for text elements.
Outcome: The proposed model can be used to estimate abnormal returns of companies when compared to titles and abstracts.

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