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Merge pull request #1 from Cary0x/main
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@@ -39,9 +39,9 @@ <h2>Abstract</h2>
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computing enclaves, an intelligent PolyModal routing system, and adaptive payment rails for compute resources.
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</p>
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<p>
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Central to StackNet is the <strong>xRouter</strong>, an intelligent routing system that dynamically selects
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Central to StackNet is the <strong>XRouter</strong>, an intelligent routing system that dynamically selects
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the most suitable model for each query based on task complexity, cost constraints, and performance requirements.
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The router implements over 9 distinct routing strategies organized into three categories: stateless routing, tool rounting (agent),
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The router implements over 9 distinct routing strategies organized into three categories: stateless routing, tool routing (agent),
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and session routers that adapt to ongoing contexts. These strategies encompass
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techniques including sematic caching, matrix factorization, KNN-similarity matching, SVM classification,
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graph-based routing for dependency resolution and Elo/BERT based signaling.
@@ -63,8 +63,8 @@ <h2>Abstract</h2>
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<p>
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The architecture extends through a <strong>co-processor framework</strong> that enables specialized execution
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units to handle domain-specific tasks. Co-processors include the Arena co-processor for competitive model
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evaluation and ranking (used by xRouter), the MetaStream co-processor for real-time metadata aggregation, the Tool co-processor
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for orchestrating MetaModel server invocations, the Agent co-processor for managing autonomous agent lifecycles,
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evaluation and ranking (used by XRouter), the MetaStream co-processor for real-time metadata aggregation, the Tool co-processor
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for orchestrating MetaModel server invocations, the agent co-processor for managing autonomous agent lifecycles,
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and the Points co-processor for tracking reputation and reward distributions. Each co-processor operates as
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an independent module that can be composed into complex execution pipelines.
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</p>
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</p>
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<p>
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The router implements a comprehensive taxonomy of <strong>9 routing strategies</strong> organized into
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three major categories. <em>stateless routing</em> which make stateless decisions using techniques such as
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three major categories. <em>Stateless routing</em> makes stateless decisions using techniques such as
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KNN similarity matching against sematic cache, SVM classification boundaries learned from labeled
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task-model pairs, and data trained on vae/embedding representations. <em>Tool rounting (agent)</em>
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extend this by maintaining conversation context, enabling more nuanced decisions as dialogues progress,
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task-model pairs, and data trained on VAE/embedding representations. <em>Tool routing (agent)</em>
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extends this by maintaining conversation context, enabling more nuanced decisions as dialogues progress,
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handling complex tool-use scenarios where the routing decision depends on the
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anticipated chain of tool calls.
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</p>
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<p>
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Advanced routing strategies include network-level Agent co-processor augmented <strong>Elo rating systems</strong> that continuously update model
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Advanced routing strategies include network-level agent co-processor augmented <strong>Elo rating systems</strong> that continuously update model
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rankings based on pairwise comparison outcomes, <strong>graph-based routing</strong> for resolving task
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dependencies and orchestrating multi-step workflows, <strong>BERT-based semantic routing</strong> that
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understands query intent at a deep level, and <strong>hybrid probabilistic methods</strong> that combine

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