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.
Generating cad code with vision-language models for 3d designs
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
roles
background 1polarities
background 1representative citing papers
CADBench is a multimodal benchmark for CAD program generation that shows specialized mesh-to-CAD models outperform general vision-language models but degrade with complexity and modality shifts.
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.
CMAG combines 3D concept scaffolding, prompt decomposition, taxonomy routing, hybrid retrieval, and agentic VLM verification to assemble topologically consistent avatars from catalog assets given free-form text prompts.
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.
citing papers explorer
-
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.
-
CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation
CADBench is a multimodal benchmark for CAD program generation that shows specialized mesh-to-CAD models outperform general vision-language models but degrade with complexity and modality shifts.
-
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.
-
CMAG: Concept-Scaffolded Retrieval for Marketplace Avatar Generation
CMAG combines 3D concept scaffolding, prompt decomposition, taxonomy routing, hybrid retrieval, and agentic VLM verification to assemble topologically consistent avatars from catalog assets given free-form text prompts.
-
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.
- Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback