Papers by Huaao Zhang
Understanding and Improving the Robustness of Terminology Constraints in Neural Machine Translation (2023.acl-long)
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| Challenge: | Existing terminology constraint test sets are blind to this issue due to oversimplified settings . PH methods retain high constraint accuracy but lower translation quality . |
| Approach: | They propose a method that replaces terminology terms with ordered labels . placeholder methods are better at retaining high constraint accuracy but lower translation quality . |
| Outcome: | The proposed method achieves high accuracy and translation quality regardless of the number or length of constraints. |
Token Drop mechanism for Neural Machine Translation (2020.coling-main)
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| Challenge: | Neural machine translation models are vulnerable to unfamiliar inputs. |
| Approach: | They propose to drop tokens of the input sentences to improve generalization and avoid overfitting for the NMT model. |
| Outcome: | The proposed approach improves on Chinese-English and English-Romanian benchmarks and achieves significant performance improvements over baselines. |