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标题为英语MEA: A Reward-Driven Multi-Agent System for Faithful Model Explanations

Recent years have seen the employment of a plethora of machine learning (ML) models in high-stakes domains, but they remain largely opaque to the practitioners who act on their predictions. While post-hoc explanation methods offer a lens into this model behavior, wielding them…

arXiv — cs.AI作者: Yuyang Cheng, Raghav Kaushik Ravi, Srivarshinee Sridhar, Sriparna Saha, Akash Ghosh, Chirag Agarwal2026年10月5日 (10月5日)
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  • Recent years have seen the employment of a plethora of machine learning (ML) models in high-stakes domains, but they remain largely opaque to the practitioners who act on their predictions
  • While post-hoc explanation methods offer a lens into this model behavior, wielding them…
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MEA: A Reward-Driven Multi-Agent System for Faithful Model Explanations

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