Papers by Nada Aldarrab
Translating Translationese: A Two-Step Approach to Unsupervised Machine Translation (P19-1)
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| Challenge: | Using a dictionary, given a rough, target language natives can uncover the latent, fully-fluent rendering of the translation. |
| Approach: | They propose a method that breaks translation into two steps by generating a dictionary and then ‘translating’ the resulting pseudo-translation into a fully fluent translation. |
| Outcome: | The proposed method 'gets better translation results on high-resource languages than previously published unsupervised MT studies' |
Segmenting Numerical Substitution Ciphers (2022.emnlp-main)
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| Challenge: | Existing methods for deciphering historical substitution ciphers are difficult to crack . cipheries that are not segmented are still difficult to deciphere . |
| Approach: | They propose automatic methods to segment historical substitution ciphers using BPE and unigram language models. |
| Outcome: | The proposed methods achieve an average segmentation error of 2% on 100 monoalphabetic ciphers and 27% on 3 real historical homophonic cipheries. |
Can Sequence-to-Sequence Models Crack Substitution Ciphers? (2021.acl-long)
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| Challenge: | Current methods for deciphering historical ciphers use beam search and a neural language model . but, this approach assumes that the target plaintext language is known . |
| Approach: | They propose an end-to-end multilingual decipherment model that can solve 1:1 substitution ciphers without explicit language identification. |
| Outcome: | The proposed model can decipher text without explicit language identification while still being robust to noise. |