arXiv — NLP / Computation & Language · · 3 min read

PatchBoard: Schema-Grounded State Mutation for Reliable and Auditable LLM Multi-Agent Collaboration

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Computer Science > Computation and Language

arXiv:2605.29313 (cs)
[Submitted on 28 May 2026]

Title:PatchBoard: Schema-Grounded State Mutation for Reliable and Auditable LLM Multi-Agent Collaboration

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Abstract:LLM multi-agent systems often coordinate through natural-language dialogue or loosely structured shared memory, making intermediate state difficult to validate, attribute, and audit. We introduce PatchBoard, a schema-grounded collaboration architecture that replaces inter-agent dialogue with validated JSON Patch mutations over a shared structured state. An Architect agent constructs a task-specific schema and workflow rules, while a deterministic kernel validates each proposed state mutation against schema constraints, role-specific write contracts, and runtime invariants before committing it transactionally. On 630 matched ALFWorld episodes, PatchBoard achieves an 84.6% success rate, compared with 30.8% for LangGraph and 61.6% for Flock, while reducing tokens per successful task to 45.5k, compared with 368.3k and 64.2k, respectively.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2605.29313 [cs.CL]
  (or arXiv:2605.29313v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2605.29313
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Shuyu Zhang [view email]
[v1] Thu, 28 May 2026 03:43:22 UTC (554 KB)
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