Papers with alignment and
Effectively Aligning and Filtering Parallel Corpora under Sparse Data Conditions (2020.acl-srw)
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| Challenge: | Parallel corpora are key to developing good machine translation systems, but abundant parallel data is hard to come by for languages with a low number of speakers. |
| Approach: | They propose an unsupervised alignment method that can handle rich morphology by removing incorrect translations and segments containing extraneous data. |
| Outcome: | The proposed method maximizes the number of correctly translated segments in a corpus and minimises noise by removing incorrect translations and segments containing extraneous data. |
Compositional Generalization by Factorizing Alignment and Translation (2020.acl-srw)
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| Challenge: | a crucial property underlying the expressive power of human language is its systematicity. |
| Approach: | They propose to make an analogous separation between alignment and translation in neural machine translation to capture compositional structure. |
| Outcome: | The proposed architecture outperforms existing neural networks on a compositional generalization task without supervision. |
Target Foresight Based Attention for Neural Machine Translation (N18-1)
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| Challenge: | Empirical experiments on Chinese-to-English and Japanese-to English datasets show that the proposed attention model delivers significant improvements in terms of alignment error rate and BLEU. |
| Approach: | They propose to explicitly access the target foresight word in the attention model to improve alignment and translation accuracy. |
| Outcome: | Empirical results show that the proposed model improves alignment error rate and BLEU on Chinese-to-English and Japanese-toEnglish datasets. |
Building Comparable Corpora for Assessing Multi-Word Term Alignment (2022.lrec-1)
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| Challenge: | Existing methods to extract bilingual terminologies from corpora are limited . MWTs pose serious challenges for alignment and machine translation systems . |
| Approach: | They propose an approach to build comparable corpora and bilingual term dictionaries that evaluate bilingual term alignment in comparable corpus. |
| Outcome: | The proposed method is validated on an existing dataset and manually annotated data. |
Representation Alignment and Adversarial Networks for Cross-lingual Dependency Parsing (2024.findings-emnlp)
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| Challenge: | Pre-trained language models have improved dependency parsing accuracy in resource-rich languages . however, the accuracy drops sharply when the model is transferred to low-resource language . |
| Approach: | They propose a representation alignment and adversarial model to filter out useful knowledge from rich-resource language and ignore useless ones. |
| Outcome: | The proposed model outperforms baseline models on the benchmark datasets by 1.37 LAS and 1.34 UAS. |
A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing (2021.emnlp-main)
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| Challenge: | Abstract Meaning Representations (AMR) represents sentence meaning as a directed acyclic graph. |
| Approach: | They propose to treat alignment and segmentation as latent variables and induce them as part of end-to-end training. |
| Outcome: | The proposed model achieves significant performance gains over a 'greedy' segmentation heuristic. |