AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work formalizes collaborative problem solving as block optimization as block optimization: each agent improves one part of a shared solution, guided by its local objective plus a correction for how its changes affect the other parts.
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....
The results suggest that simple pruning-inspired orderings can provide useful fixed sparse supports for PEFT, especially when combined with low-rank adapters.
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