Papers with word alignment accuracy

2 papers
A Supervised Word Alignment Method based on Cross-Language Span Prediction using Multilingual BERT (2020.emnlp-main)

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Challenge: supervised word alignment tools such as GIZA++, MGIZA (Gao and Vogel, 2008) and FastAlign remain stagnant in terms of word alignment accuracy.
Approach: They propose a supervised word alignment method based on cross-language span prediction by formalizing a word alignment problem as a collection of independent predictions from a token in the source sentence to a span in the target sentence.
Outcome: The proposed method significantly outperforms previous supervised and unsupervised word alignment methods without any bitexts for pretraining.
Improving Latent Alignment in Text Summarization by Generalizing the Pointer Generator (D19-1)

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Challenge: Modern pointer generators only capture exact word matches, ignoring possible inflections or abstractions, which restricts its power of capturing richer latent alignment.
Approach: They propose a pointer generator architecture that allows the model to "edit" pointed tokens instead of always copying them.
Outcome: The proposed model captures more latent alignment relations than exact word matches and generates higher-quality summaries validated by both qualitative and quantitative evaluations.

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