{"paper":{"title":"LLM4CAD-Editor: An Intent-Aware Large Language Model Framework for Multi-Level Computer-Aided Design Editing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Yuewan Sun, Zhenghui Sha","submitted_at":"2026-05-21T23:35:15Z","abstract_excerpt":"Large language models (LLMs) have recently enabled automatic generation of parametric computer-aided design (CAD) programs from natural language. However, real-world CAD workflows are inherently iterative and require reliable editing rather than one-shot model synthesis. In this work, we propose LLM4CAD-Editor, an LLM-based intent-aware framework for instruction-guided CAD editing based on a structured domain-specific language (LLM4CAD-DSL). The symbolic representation of LLM4CAD-DSL enables robust geometric modification through a feature-level entity selection mechanism, allowing models to re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.20607","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.20607/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}