Papers with offline compression methods
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models (2023.findings-eacl)
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| Challenge: | Recent transformer language models achieve outstanding results on many downstream tasks, but their enormous size often makes them impractical on memory-constrained devices. |
| Approach: | They propose an offline compression approach that reduces the complexity of the model by enabling collaboration between modules. |
| Outcome: | The proposed approach outperforms commonly used factorization-based offline compression methods on various NLP tasks. |