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Found 9 papers, 1 papers with code
Understanding Multi-Head Attention in Abstractive Summarization
Finally, we find that relative positions heads seem integral to summarization performance and persistently remain after pruning.
Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?
We investigate whether distributions calculated by different attention heads in a transformer architecture can be used to improve transparency in the task of abstractive summarization.
Dynamic Data Selection for Neural Machine Translation
Intelligent selection of training data has proven a successful technique to simultaneously increase training efficiency and translation performance for phrase-based machine translation (PBMT).
A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation
A major challenge for statistical machine translation (SMT) of Arabic-to-English user-generated text is the prevalence of text written in Arabizi, or Romanized Arabic.
Measuring the Effect of Conversational Aspects on Machine Translation Quality
Finally, we find that male speakers are harder to translate and use more vulgar language than female speakers, and that vulgarity is often not preserved during translation.
