Are queries and keys always relevant? A case study on transformer wave functions
The dot product attention mechanism, originally designed for natural language processing tasks, is a cornerstone of modern Transformers. It adeptly captures semantic relationships between word pairs in sentences by computing a similarity overlap between queries and keys. In this work, we explore the...
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Main Authors: | Riccardo Rende, Luciano Loris Viteritti |
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Format: | Article |
Language: | English |
Published: |
IOP Publishing
2025-01-01
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Series: | Machine Learning: Science and Technology |
Subjects: | |
Online Access: | https://doi.org/10.1088/2632-2153/ada1a0 |
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