MiA-Signature: Approximating Global Activation for Long-Context Understanding

• URL: http://arxiv.org/abs/2605.06416v1
• Date: Thu, 07 May 2026 15:25:02 GMT
• Title: MiA-Signature: Approximating Global Activation for Long-Context Understanding
• Abstract summary: We introduce the concept of textbfMindscape Activation Signature (MiA-Signature), a compressed representation of the global activation pattern induced by a query.<n>The resulting MiA-Signature serves as a conditioning signal that approximates the effect of the full activation state while remaining computationally tractable.
• Score: 48.9604042895266
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: A growing body of work in cognitive science suggests that reportable conscious access is associated with \emph{global ignition} over distributed memory systems, while such activation is only partially accessible as individuals cannot directly access or enumerate all activated contents. This tension suggests a plausible mechanism that cognition may rely on a compact representation that approximates the global influence of activation on downstream processing. Inspired by this idea, we introduce the concept of \textbf{Mindscape Activation Signature (MiA-Signature)}, a compressed representation of the global activation pattern induced by a query. In LLM systems, this is instantiated via submodular-based selection of high-level concepts that cover the activated context space, optionally refined through lightweight iterative updates using working memory. The resulting MiA-Signature serves as a conditioning signal that approximates the effect of the full activation state while remaining computationally tractable. Integrating MiA-Signatures into both RAG and agentic systems yields consistent performance gains across multiple long-context understanding tasks.

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