Papers by Zhong-Yi Lu
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 . |
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models (2022.coling-1)
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| Challenge: | Recent results show that the mix-of-experts architecture is parameter inefficient . large-scale pre-trained language models can achieve excellent performance in many NLP tasks. |
| Approach: | They propose to build a parameter-efficient mix-of-experts architecture by sharing information across experts. |
| Outcome: | The proposed architecture increases model capacity without increasing computation costs. |