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Attention-Augmented LSTMs for Automatic Homophonic Ciphertext Decipherment
arXiv:2606.05078v1 Announce Type: new Abstract: Homophonic substitution ciphers replace each plaintext letter with one of several possible ciphertext codes, deliberately weakening letter-frequency patterns and making automated decipherment difficult. This paper evaluates whether an attention-augmented Long Short-Term Memory (LSTM) model can learn such mappings in a historically motivated shared-key setting: all ciphertexts draw from the same known homophonic code pool, while individual keys...