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Attention Mechanism
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Attention Mechanism
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Jul 16
Overcoming Computational Challenges in Large Language Model Inference with MInference 1.0
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Apr 3
Huawei & Peking U’s DiJiang: A Transformer Achieving LLaMA2–7B Performance at 1/50th the Training Cost
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Oct 11, 2023
Yale U & Google’s HyperAttention: Long-Context Attention with the Best Possible Near-Linear Time Guarantee
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Nov 14, 2022
‘MrsFormer’ Employs a Novel Multiresolution-Head Attention Mechanism to Cut Transformers’ Compute and Memory Costs
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Mar 1, 2022
Cornell U & Google Brain’s FLASH Yields High Transformer Quality in Linear Time
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Dec 14, 2021
Google Proposes a ‘Simple Trick’ for Dramatically Reducing Transformers’ (Self-)Attention Memory Requirements
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Dec 6, 2021
Integrating Self-Attention and Convolution: Tsinghua, Huawei & BAAI’s ACmix Achieves SOTA Performance on CV Tasks…
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Nov 4, 2021
Washington U & Google Study Reveals How Attention Matrices Are Formed in Encoder-Decoder Architectures
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Aug 30, 2021
Tsinghua U & Microsoft Propose Fastformer: An Additive Attention Based Transformer With Linear Complexity
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Aug 5, 2021
Google’s H-Transformer-1D: Fast One-Dimensional Hierarchical Attention With Linear Complexity for Long Sequence…
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