Evaluating and Improving the Coreference Capabilities of Machine Translation Models (2023.eacl-main)
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| Challenge: | Currently, end-to-end models learn coreference resolution implicitly by observing aligned sentences in bilingual corpora. |
| Approach: | They develop a method that derives coreference clusters from MT output and evaluates them without requiring annotations in the target language. |
| Outcome: | The proposed model outperforms existing models on three challenging benchmarks. |
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