Contribution Weights combine attention, value magnitude, and directional alignment to measure token influence more faithfully than attention alone, and show attention sinks actively suppress information via a convex sink-rate to output-norm relationship.
Orthorank: Token selection via sink token orthogonality for efficient llm inference
2 Pith papers cite this work. Polarity classification is still indexing.
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