Sequence to Sequence Learning with Neural Networks .

Abstract

Introduced the encoder-decoder architecture for sequence-to-sequence tasks like machine translation.

Architecture

• Encoder LSTM: Reads input sequence, produces fixed-size context vector
• Decoder LSTM: Generates output sequence conditioned on context vector

Impact

Before Transformers, this was the dominant architecture for NLP tasks. Laid groundwork for attention mechanisms and modern NLP.