Papers by Heshan Liu

1 papers
Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers (2025.findings-emnlp)

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Challenge: a large computational cost for attention computation in large language models is a major obstacle .
Approach: They propose a convolution-like structure for attention computation using convolution matrices . they then propose an efficient approximation method to approximate the attention matrix .
Outcome: The proposed method achieves nearly linear time complexity in n1+o(1) time.

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