paper

Consensus-based Agentic Large Language Model Framework for Harmonized Tariff Schedule Code Classification

paperactiveprovisionalconsensus-based-agentic-large-language-model-framework-for-harmonized-tariff-schedule-code-classification-7d9716fe·1 events·first seen 33h ago

Aliases: Consensus-based Agentic Large Language Model Framework for Harmonized Tariff Schedule Code Classification

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Analytics-Everywhere-Lab

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4arXiv · cs.AI·33h ago·source ↗

Consensus-based multi-agent LLM framework for HTS tariff code classification in maritime logistics

Researchers propose a multi-agent LLM framework for classifying Canadian 10-digit Harmonized Tariff Schedule codes, targeting smart-port and maritime logistics applications. The system combines semantic retrieval over official tariff documents, consensus-based validation, element-wise voting across hierarchical code components, and human-in-the-loop escalation. Evaluated on 3,300 expert-labeled product records, results show exact 10-digit classification remains difficult even for advanced LLMs, with accuracy degrading at finer granularity levels. The work argues for uncertainty-aware, evidence-grounded workflows over fully autonomous classification.

Enterprise Deployment Patterns Agent and Tool Ecosystem Consensus-based Agentic Large Language Model Framework for Harmonized Tariff Schedule Code Classification Analytics-Everywhere-Lab