Papers by Takeshi Suzuki
OptiPrune: Effective Pruning Approach for Every Target Sparsity (2025.coling-main)
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| Challenge: | Existing methods for model pruning only perform optimally within specific sparsity ranges. |
| Approach: | They propose a pruning method that reduces model size by eliminating redundant parameters . they compare it with OptiPrune, which adapts non-uniform sparsity with adaptive deviation . |
| Outcome: | The proposed method reduces model size and maintains performance despite large size and high computational demands. |