Who Are You Explaining To? A Multi-Agent System for Audience-Aware XAI Narratives
3.20T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.11033.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryPaper introduces XstrAI, a multi-agent framework that converts SHAP feature-attribution outputs into audience-tailored narratives for patients, clinicians, and data scientists. It uses immutable shared evidence and three specialized LLM agents (planning, linguistic realization, validation) with a bounded revision loop, evaluated on diabetes and stroke risk prediction against 11 baselines.
Why it mattersThe immutable-evidence-plus-validator pattern is a reusable multi-agent design where faithfulness to source data is enforced structurally rather than prompted.
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