Encoder-decoder architectures are a type of neural network design used for transforming input data into a different representation, typically for tasks such as machine translation and image captioning. In these architectures, the encoder processes the input to compress its information into a fixed-length representation, while the decoder interprets this representation to generate output, making them essential for tasks that require understanding and generating sequences or structured data.
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