Sequence-to-sequence models

A class of machine learning models that converts one sequence of data into another. It learns patterns and relationships in the input sequence, then uses them to produce an output sequence.

Example

Sequence-to-sequence models are often used in machine translation. Given a sentence in one language, the model encodes the input sentence to capture its meaning and structure. It then decodes that representation to generate a sentence in the target language while preserving the original meaning and context.