Papers by Baikjin Jung
Bring More Attention to Syntactic Symmetry for Automatic Postediting of High-Quality Machine Translations (2023.acl-short)
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| Challenge: | Existing APE systems are not good at handling high-quality MTs even for a language pair with abundant data resources, English–German. |
| Approach: | They propose a linguistically motivated method of regularization that encourages symmetric self-attention on the given MT. |
| Outcome: | The proposed method improves the state-of-the-art architecture’s APE quality for high-quality MTs. |
Adaptation of Back-translation to Automatic Post-Editing for Synthetic Data Generation (2021.eacl-main)
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| Challenge: | Automated Post-Editing (APE) aims to correct errors in the output of a given machine translation system. |
| Approach: | They propose two new methods of synthesizing additional MT outputs by adapting back-translation to the APE task, obtaining robust enlargements of existing synthetic APE training dataset. |
| Outcome: | The proposed methods improve translation quality on the English-German APE task by enlarging the existing training dataset. |
Denoising Table-Text Retrieval for Open-Domain Question Answering (2024.lrec-main)
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| Challenge: | Existing studies in table-text open-domain question answering have problems with false-positive labels in training datasets. |
| Approach: | They propose a denoised table-text retriever that discards false positives from training datasets . they integrate table-level ranking information into the retriever to assist in finding evidence . |
| Outcome: | The proposed method outperforms baselines on retrieval recall and QA tasks. |