The Encoder-Decoder architecture is widely used in sequence ... which can lead to information loss. Attention mechanisms were introduced to mitigate this problem by allowing the model to focus on ...

For example, you might use an attention mechanism ... Choosing the best encoder-decoder architecture for your seq2seq model is not a trivial task. It depends on many factors, such as the input ...

The objective of this project is to train a seq2seq model (an encoder-decoder model with attention) for machine translation. This project is motivated by the idea of implementing an advanced ...

encoder-decoder, causal decoder, and prefix decoder. Each architecture type exhibits distinct attention patterns. Based on the vanilla Transformer model, the encoder-decoder architecture consists of ...

To this end, we introduce, a multi-scale encoder-decoder self-attention (MEDUSA ... representational abstractions throughout the network architecture which can help to model the scale-specific ...

In this paper, a high-efficiency encoder-decoder structure, inspired by the top-down attention mechanism in human brain perception ... Experiments show that the proposed method effectively reduces ...

insufficient attention to detail information, and discrepancies between training objectives and evaluation indicators. To address these issues, this paper studies and optimizes the image caption model ...