Papers with decipherment methods
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. |