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Evidence record 37 · automatically gathered

Constraint-Aware Hierarchical Search for Regulation-Driven Fine-Grained Classification

Tasks such as customs tariff classification, export control categorization, and standards-based equipment coding require assigning an input instance to a fine-grained class under an explicit regulatory hierarchy. Unlike standard text classification, the correct label in these tasks is not determined by semantic similarity alone, but by rule-defined boundaries, threshold conditions, exclusion clauses, definitions, and local exceptions. As a result, two highly similar inputs may require different

Record details

Published: 12 July 2026
Source: arXiv
Category: Research
Topics: Regulation
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Regulation

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Shared topic: Regulation

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How to cite this record

ethics.ai (12 July 2026), “Constraint-Aware Hierarchical Search for Regulation-Driven Fine-Grained Classification,” evidence record 37, https://ethics.ai/record/37 (originally published by arXiv).

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