FllumaOne releases 100,000 kernel-validated CAD models as executable Python programs with aligned multimodal data including feature histories and geometry exports.
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Cad-mllm: Unifying multimodality-conditioned cad generation with mllm
19 Pith papers cite this work. Polarity classification is still indexing.
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BRepCLIP is the first contrastive pretraining framework that tokenizes BRep CAD geometry into surface and curve vocabularies and aligns the resulting embeddings with CLIP text and image encoders, reporting large gains in retrieval and zero-shot classification over point-based baselines.
UniCAD supplies a unified multi-modal benchmark and an end-to-end MLLM that performs reconstruction, generation, and QA on CAD data, reporting SOTA results on UniCAD and Fusion360.
MUSE is a new benchmark and three-stage evaluation protocol for text-to-CAD generation that assesses functionality, manufacturability, and assemblability of B-Rep assemblies beyond geometric similarity.
BrepForge factorizes B-rep synthesis into face-aware autoregressive wireframe composition followed by boundary-conditioned surface instantiation using learning-free geometric priors.
Img2CADSeq generates standard CAD sequences from images via a multi-stage pipeline with three-level hierarchical codebook encoding, importance-guided compression, and contrastive point-cloud conditioning of a VQ-Diffusion model, outperforming prior methods on new CAD-220K and PrintCAD datasets.
AssemblyBench dataset and AssemblyDyno transformer model enable physics-aware prediction of assembly sequences and trajectories for complex industrial objects from multimodal instructions and 3D shapes.
CADBench is a new multimodal benchmark for CAD program generation that combines 18k samples from DeepCAD, Fusion 360, ABC, MCB, and Objaverse across clean/noisy meshes and various renders, used to test 11 models and reveal failure modes.
ArtiCAD presents the first training-free multi-agent framework that generates articulated, editable CAD assemblies from text or images by predicting assembly relationships early and using validation with rollback.
CAD-Coder generates valid CadQuery scripts from text via supervised fine-tuning followed by reinforcement learning with geometric Chamfer Distance rewards and chain-of-thought planning.
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.
A hybrid agentic architecture integrates knowledge-based physical verification tools into LLM-driven CAD design loops, producing more complex and functionally valid designs than prior agentic baselines.
CADFit recovers complex editable CAD construction sequences from meshes via IoU-driven hybrid optimization over structured programs, outperforming prior methods on volumetric IoU, Chamfer Distance, and invalid ratio.
AADvark extends agent-aided CAD design to dynamic 3D assemblies with movable parts by integrating constraint solvers and visual feedback to create a verification signal for the agent.
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.
Pointer-CAD v2 decouples planning from construction in LLM-based CAD generation by using a pointer mechanism to reference continuous parameters from a design plan, paired with new hierarchical accuracy metrics.
Memory-augmented RL agent with case and skill libraries plus dynamic retrieval improves success rate and geometric consistency for complex CAD model generation.
CADDesigner is an LLM agent that generates conceptual CAD models from text and sketches via requirement analysis, the ECIP paradigm, and iterative visual feedback, outperforming baselines in experiments.
Hunyuan3D 2.0 scales flow-based diffusion transformers and texture synthesis models to generate high-resolution textured 3D assets that outperform prior state-of-the-art in geometry, alignment, and texture quality.
citing papers explorer
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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.
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BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understanding
BRepCLIP is the first contrastive pretraining framework that tokenizes BRep CAD geometry into surface and curve vocabularies and aligns the resulting embeddings with CLIP text and image encoders, reporting large gains in retrieval and zero-shot classification over point-based baselines.
-
UniCAD: A Unified Benchmark and Universal Model for Multi-Modal Multi-Task CAD
UniCAD supplies a unified multi-modal benchmark and an end-to-end MLLM that performs reconstruction, generation, and QA on CAD data, reporting SOTA results on UniCAD and Fusion360.
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MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation
MUSE is a new benchmark and three-stage evaluation protocol for text-to-CAD generation that assesses functionality, manufacturability, and assemblability of B-Rep assemblies beyond geometric similarity.
-
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.
-
Img2CADSeq: Image-to-CAD Generation via Sequence-Based Diffusion
Img2CADSeq generates standard CAD sequences from images via a multi-stage pipeline with three-level hierarchical codebook encoding, importance-guided compression, and contrastive point-cloud conditioning of a VQ-Diffusion model, outperforming prior methods on new CAD-220K and PrintCAD datasets.
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AssemblyBench: Physics-Aware Assembly of Complex Industrial Objects
AssemblyBench dataset and AssemblyDyno transformer model enable physics-aware prediction of assembly sequences and trajectories for complex industrial objects from multimodal instructions and 3D shapes.
-
CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation
CADBench is a new multimodal benchmark for CAD program generation that combines 18k samples from DeepCAD, Fusion 360, ABC, MCB, and Objaverse across clean/noisy meshes and various renders, used to test 11 models and reveal failure modes.
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ArtiCAD: Articulated CAD Assembly Design via Multi-Agent Code Generation
ArtiCAD presents the first training-free multi-agent framework that generates articulated, editable CAD assemblies from text or images by predicting assembly relationships early and using validation with rollback.
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CAD-Coder: Text-to-CAD Generation with Chain-of-Thought and Geometric Reward
CAD-Coder generates valid CadQuery scripts from text via supervised fine-tuning followed by reinforcement learning with geometric Chamfer Distance rewards and chain-of-thought planning.
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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.
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Physics-in-the-Loop: A Hybrid Agentic Architecture for Validated CAD Engineering Design
A hybrid agentic architecture integrates knowledge-based physical verification tools into LLM-driven CAD design loops, producing more complex and functionally valid designs than prior agentic baselines.
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CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimization
CADFit recovers complex editable CAD construction sequences from meshes via IoU-driven hybrid optimization over structured programs, outperforming prior methods on volumetric IoU, Chamfer Distance, and invalid ratio.
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Agent-Aided Design for Dynamic CAD Models
AADvark extends agent-aided CAD design to dynamic 3D assemblies with movable parts by integrating constraint solvers and visual feedback to create a verification signal for the agent.
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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.
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Pointer-CAD v2: Plan-Then-Construct CAD Generation with Dimension-Aware Parametric Precision
Pointer-CAD v2 decouples planning from construction in LLM-based CAD generation by using a pointer mechanism to reference continuous parameters from a design plan, paired with new hierarchical accuracy metrics.
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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.
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CADDesigner: Conceptual CAD Model Generation with a General-Purpose Agent
CADDesigner is an LLM agent that generates conceptual CAD models from text and sketches via requirement analysis, the ECIP paradigm, and iterative visual feedback, outperforming baselines in experiments.
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Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
Hunyuan3D 2.0 scales flow-based diffusion transformers and texture synthesis models to generate high-resolution textured 3D assets that outperform prior state-of-the-art in geometry, alignment, and texture quality.