Handbook.md shows that long policy documents do not reliably govern agents
A new research paper titled 'HANDBOOK.md' explores the limitations of using long policy documents to govern AI agents. The study suggests that such documents do not reliably ensure instruction following for agentic systems.
Why it matters
As AI agents become more autonomous, understanding the reliability of governance frameworks is critical for safety and alignment.
Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Sushant Mehta [ view email ] [v1] Tue, 28 Jul 2026 07:58:07 UTC (57 KB) Full-text links: Access Paper: View a PDF of the paper titled HANDBOOK.md: A Benchmark for Long-Context Agentic Instruction Following, by Liudas Panavas and 6 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.AI < prev | next > new | recent | 2026-07 Change to browse by: cs cs.CL References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations?
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