RPA-Check is a new multi-stage framework using dimension definition, boolean checklist augmentation, semantic filtering, and LLM-as-judge verification to assess role-playing agents, with tests on a legal training game showing smaller instruction-tuned models can be more consistent than larger ones.
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
ACE routes patent claims via error-type entropy to a schema-constrained LLM, claiming better accuracy than a supervised 70B model at 78% lower cost.
citing papers explorer
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RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents
RPA-Check is a new multi-stage framework using dimension definition, boolean checklist augmentation, semantic filtering, and LLM-as-judge verification to assess role-playing agents, with tests on a legal training game showing smaller instruction-tuned models can be more consistent than larger ones.
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Adaptive Cost-Efficient Evaluation for Reliable Patent Claim Generation
ACE routes patent claims via error-type entropy to a schema-constrained LLM, claiming better accuracy than a supervised 70B model at 78% lower cost.