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Contribution Weights: A Geometrical Analysis of Self-Attention Transformers

arXiv cs.LG · 2026-06-09 Cached

Introduces Contribution Weights, a projection-based metric that accounts for attention weight, value magnitude, and directional alignment to more faithfully measure token importance in transformer LLMs, revealing active functional roles of attention sinks.

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