FllumaOne releases 100,000 kernel-validated CAD models as executable Python programs with aligned multimodal data including feature histories and geometry exports.
and Desai, Nishkrit and Willis, Karl D
9 Pith papers cite this work. Polarity classification is still indexing.
9
Pith papers citing it
years
2026 9verdicts
UNVERDICTED 9representative citing papers
BrepForge factorizes B-rep synthesis into face-aware autoregressive wireframe composition followed by boundary-conditioned surface instantiation using learning-free geometric priors.
Text2CAD-Bench supplies 600 dual-prompt examples across four geometric and domain levels to test LLMs on text-to-parametric CAD, finding solid basic performance but sharp drops on complex topology and advanced features.
MV-GEL localizes fine-grained geometric entities on 3D meshes from natural language by ranking informative views with GELviews, applying VLM segmentation, and lifting masks via geometry-aware ray casting, reporting up to 1.7X face IoU and 4.5X edge F1 gains over baselines.
IterCAD is a multimodal agent framework using progressive SFT and geometry-aware RL for CAD tasks, with a new data pipeline, IterCAD-Bench, and CD-TR metric showing outperformance in executability and precision.
Pointer-CAD unifies B-Rep geometry with command sequences via pointer-based entity selection, allowing LLMs to perform complex CAD edits while cutting topological errors from quantization.
Memory-augmented RL agent with case and skill libraries plus dynamic retrieval improves success rate and geometric consistency for complex CAD model generation.
An extrusion segmentation strategy decomposes CAD models into partial shapes to increase data diversity and improve deep learning reconstruction from point clouds.
The paper classifies AI+CAD data representations and argues WHUCAD's three-level architecture provides better foundational support for industrial parametric feature modeling than DeepCAD.
citing papers explorer
-
FllumaOne: A Code-Native Multimodal CAD Dataset with Executable Programs and Kernel-Validated Feature Histories
FllumaOne releases 100,000 kernel-validated CAD models as executable Python programs with aligned multimodal data including feature histories and geometry exports.
-
BrepForge: Factorized B-rep Synthesis via Wireframe Composition and Boundary-Conditioned Surface Instantiation
BrepForge factorizes B-rep synthesis into face-aware autoregressive wireframe composition followed by boundary-conditioned surface instantiation using learning-free geometric priors.
-
Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generation
Text2CAD-Bench supplies 600 dual-prompt examples across four geometric and domain levels to test LLMs on text-to-parametric CAD, finding solid basic performance but sharp drops on complex topology and advanced features.
-
MV-GEL: Language-Driven Multi-View Geometric Entity Localization on Meshes
MV-GEL localizes fine-grained geometric entities on 3D meshes from natural language by ranking informative views with GELviews, applying VLM segmentation, and lifting masks via geometry-aware ray casting, reporting up to 1.7X face IoU and 4.5X edge F1 gains over baselines.
-
IterCAD: An Iterative Multimodal Agent for Visually-Grounded CAD Generation and Editing
IterCAD is a multimodal agent framework using progressive SFT and geometry-aware RL for CAD tasks, with a new data pipeline, IterCAD-Bench, and CD-TR metric showing outperformance in executability and precision.
-
Pointer-CAD: Unifying B-Rep and Command Sequences via Pointer-based Edges & Faces Selection
Pointer-CAD unifies B-Rep geometry with command sequences via pointer-based entity selection, allowing LLMs to perform complex CAD edits while cutting topological errors from quantization.
-
Memory-Augmented Reinforcement Learning Agent for CAD Generation
Memory-augmented RL agent with case and skill libraries plus dynamic retrieval improves success rate and geometric consistency for complex CAD model generation.
-
Extrusion Segmentation Strategy to improve CAD Reconstruction from Point Cloud
An extrusion segmentation strategy decomposes CAD models into partial shapes to increase data diversity and improve deep learning reconstruction from point clouds.
-
AI+CAD Data Representation Architecture: From DeepCAD Solid Modeling to WHUCAD Industrial-Level Parametric Feature Modeling
The paper classifies AI+CAD data representations and argues WHUCAD's three-level architecture provides better foundational support for industrial parametric feature modeling than DeepCAD.