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README.md CHANGED
@@ -502,6 +502,7 @@ This section focuses on durable loop state and cross-run context. For context-wi
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  - 🧰 **Tool** [Eve](https://github.com/vercel/eve) - Vercel's TypeScript-native agent framework with durable execution, sandboxed compute, and OpenTelemetry tracing built in, so recurring agent work persists, replays, and is observable across runs by default.
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  - 📄 **Paper** [Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework](https://arxiv.org/abs/2603.11445) - Decomposes work into a dependency-aware DAG, runs domain agents in parallel, and uses an LLM verifier to drive adaptive replanning with configurable stop conditions, the verify-and-replan core of a reliable loop.
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  - 📄 **Paper** [From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents](https://arxiv.org/abs/2603.22386) - Organizes how agent workflows are fixed ahead of time or generated and revised per run, and which evaluation signals drive that choice, a map of the design space for recurring loops.
 
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  ## Benchmarks And Evaluation
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  - 🧰 **Tool** [Eve](https://github.com/vercel/eve) - Vercel's TypeScript-native agent framework with durable execution, sandboxed compute, and OpenTelemetry tracing built in, so recurring agent work persists, replays, and is observable across runs by default.
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  - 📄 **Paper** [Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework](https://arxiv.org/abs/2603.11445) - Decomposes work into a dependency-aware DAG, runs domain agents in parallel, and uses an LLM verifier to drive adaptive replanning with configurable stop conditions, the verify-and-replan core of a reliable loop.
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  - 📄 **Paper** [From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents](https://arxiv.org/abs/2603.22386) - Organizes how agent workflows are fixed ahead of time or generated and revised per run, and which evaluation signals drive that choice, a map of the design space for recurring loops.
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+ - 🧰 **Tool** [Agent-as-a-Router](https://github.com/LanceZPF/agent-as-a-router) - Agentic model routing for coding agents reframed as a context-action-feedback loop (ACRouter: orchestrator, verifier, memory) that learns which LLM to route each task to from execution feedback rather than frozen priors, with the CodeRouterBench benchmark across 8 frontier models.
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  ## Benchmarks And Evaluation
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