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Peter Richtárik

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#machine learning Preprint Oct 2026

QK-Wanda: Coupling Queries and Keys for Unstructured Pruning

Wanda (Sun et al., 2024) prunes large language models by scoring weights independently within each linear projection, although queries and keys interact through dot products. We introduce QK-Wanda, which scores query and key weights by their individual deletion costs under an unmasked pre-RoPE reconstruction objective....

Ivan D. Ilin, Peter Richtárik · 0 citations
Jul 2026

Super-Tuning: From Activation-Aware Pruning to Sparse Fine-Tuning

The results suggest that simple pruning-inspired orderings can provide useful fixed sparse supports for PEFT, especially when combined with low-rank adapters.

Ivan D. Ilin, Philip Zmushko, Peter Richtárik · 0 citations

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