ASMR: Agentic Schema Generation for Ship Maintenance Report Writing
In this paper, we study the automatic schema generation problem: given a collection of historical ship maintenance and operational reports across multiple form categories, automatically discover compact and informative schemas that capture the essential information requirements of each report type. To address this challenge, we propose ASMR, a modular agentic framework consisting of two specialized agents. A Field Generation Agent extracts semantic concepts from historical narratives and generates candidate schema fields through adaptive multi-granularity clustering, while a Structural Optimizer Agent employs reinforcement learning to identify compact, informative, and non-redundant schem...
| Authors | Sohrab Namazi Nia, Amogh Dalal, Ning Sa et al. |
|---|---|
| Primary category | cs.AI |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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