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pith:2025:RXUBIQBL4537SBTTFUCHHI67CJ
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HistCAD: A Constraint-Aware Parametric History-Based CAD Representation, Dataset, and Benchmark with Industrial Complexity

Chuanyang Li, Chuqi Han, Hailong Shen, Jiaxin Jing, Peng Zheng, Xintong Dong, Yanzhi Song, Zhouwang Yang

Explicit constraints in parametric CAD sequences preserve design intent after parameter edits.

arxiv:2602.19171 v3 · 2025-12-08 · cs.GR · cs.AI

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Claims

C1strongest claim

Experiments show that explicit constraints are essential for preserving design intent after edits, and that HistCAD supports supervised CAD generation from text and direct LLM workflows.

C2weakest assumption

The introduced metrics (Edit Reachability, conditional preserved constraint satisfaction, Overall Editable Success) and the dataset alignment with native CAD models sufficiently capture real-world design intent preservation and industrial complexity.

C3one line summary

HistCAD provides a constraint-aware parametric CAD representation, a dataset of 170k industrial sequences, and an editability benchmark with metrics ER, cPCSR, and OES to evaluate preservation of design intent.

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First computed 2026-06-01T01:02:35.202344Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

8de814402be777f906732d0473a3df127fc643cf52530de087ca940b81ee82b4

Aliases

arxiv: 2602.19171 · arxiv_version: 2602.19171v3 · doi: 10.48550/arxiv.2602.19171 · pith_short_12: RXUBIQBL4537 · pith_short_16: RXUBIQBL4537SBTT · pith_short_8: RXUBIQBL
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/RXUBIQBL4537SBTTFUCHHI67CJ \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
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Canonical record JSON
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