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The article analyzes token distribution in AI agent sessions, noting that most tokens go to context and tool results rather than final output, suggesting that not all need frontier models.
This paper investigates how semantic information is distributed across textual tokens in text-to-image models, finding that information concentration and cross-item interactions significantly affect image generation alignment. The authors use patching techniques to demonstrate that simple encoding-stage interventions can improve alignment quality.