Papers with stacked network architectures

1 papers
Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators (2021.acl-long)

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Challenge: Existing methods for pre-trained language models (PLMs) use parameter reduction techniques.
Approach: They propose a pre-trained language model compression approach based on the matrix product operator from quantum many-body physics.
Outcome: The proposed approach can decompose an original matrix into central tensors and auxiliary tenses . it can be applied to the original or compressed PLMs in a general way, with a lighter network .

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