Papers by Takuya Matsuzaki

1 papers
Absolute Position Embedding Learns Sinusoid-like Waves for Attention Based on Relative Position (2023.emnlp-main)

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Challenge: Attention weight is a clue to interpret how a Transformer-based model makes an inference.
Approach: They analyze the mechanism behind the concentration of attention on nearby tokens . they find that attention in some heads is largely determined by relative positions .
Outcome: The attention weights of the self-attention in a Transformer-based model are analyzed . the model can learn relationships between tokens while allowing parallelization, they show .

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