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Found 3 papers, 1 papers with code
A Comprehensive Survey of Compression Algorithms for Language Models
How can we compress language models without sacrificing accuracy?
Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models
As a result, K-prune shows significant accuracy improvements up to 58. 02%p higher F1 score compared to existing retraining-free pruning algorithms under a high compression rate of 80% on the SQuAD benchmark without any retraining process.
Fast and Accurate Transferability Measurement for Heterogeneous Multivariate Data
We address the problem of measuring transferability between source and target datasets, where the source and the target have different feature spaces and distributions.
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