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SEEK: Skill-Routed Evaluation with Evolvable Knowledge for Industrial Search

arXiv · AI, language, vision and robotics · article · Sep 24, 2026 · UTC

Search quality evaluation provides essential supervision and diagnostic signals for the development and iteration of industrial search systems. Although large language models (LLMs) offer a scalable alternative to manual assessment, reliable automatic evaluation remains challenging: users experience search results at the page level, while the applicable evaluation criteria are multi-dimensional and continuously evolving. Packing all evaluation criteria into a unified prompt introduces irrelevant context and potential criterion interference, whereas internalizing them through post-training tigh

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