Automated Textbook Auditing with Multi-Agent LLM Systems
3.40T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2607.11276.
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 presents AI Textbook Auditor, a multi-agent LLM pipeline that audits textbooks for factual accuracy, technical correctness, and grammar via two analysis tracks plus a judge agent, demonstrated on two Romanian upper-secondary textbooks yielding 56 and 72 findings respectively.
Why it mattersConcrete multi-agent QA architecture with domain adaptation, false-positive filtering via a judge agent, and reported precision numbers — useful pattern for building review pipelines that defer final decisions to humans.
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