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📄 ResearchJune 17, 2026

Complementary Attention Head Pruning for Efficient Transformers

The remarkable success of Transformer-based models in natural language processing stems from architectural scaling, which leads to a large number of parameters and hinders deployment in resource-constrained environments. While structured pruning offers a pathway to compression, existing state-of-the...

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Source

http://arxiv.org/abs/2606.19150v1