Transformer Architecture: Implemented various Transformer components, including multi-head attention, feed-forward layers, layer normalization, encoder, and decoder blocks, following the Attention is ...

Word embeddings usually have hundreds ... languages are mapped to each other. Like the encoder module, the decoder attention vector is passed through a feed-forward layer. Its result is then ...

Word vector embeddings are just the text represented in a numerical ... encoder-only, decoder-only. Encoder-decoder attention lets the decoder consider input sequences when generating an output, while ...

However, traditional Encoder-Decoder models face challenges in handling long sequences due to the fixed-length context vector, which can lead to information loss. Attention mechanisms were introduced ...

Our model adopts the encoder-decoder model. The encoder model improved the KBGAT model with a gate mechanism to control the attention mechanism and use entity embeddings to update relation embeddings.