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LLM agents combine models with execution harnesses, so agentic benchmark performance reflects their joint behavior. We argue that harnesses should therefore be evaluated through their interactions with underlying models. We develop a framework combining five complementary measures: (i) Valid Completion Rate (VCR), how...
This paper introduces RSI-router, a routing framework that constructs subtask-level model assignments and model-specific skills through recursive self-improvement over accumulated experience and establishes a stronger performance--cost Pareto frontier than 9 routing methods.
This work presents AgentPanel, a multi-agent forum for human--AI collaboration in scientific exploration, a multi-agent forum for human--AI collaboration in scientific exploration that outperforms a centralized multi-agent debate baseline and shows that users value AgentPanel for perspective diversity and exploration s...
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