Specification-Conditioned Analog Circuit Generation with Contrastive Learning and Classifier Guidance
A variational autoencoder-based model, CktGen, that directly generates analog circuits from specified requirements by mapping circuits and specifications into a joint latent space, employing contrastive learning and classifier guidance to enhance the consistency between the two modalities.
Evaluating the Capabilities of Large Language Models for Hardware Design and Verification
Large Language Models (LLMs) can be leveraged to automate both the design and verification of hardware modules, potentially streamlining the digital design pipeline.
A Semi-Automatic Tool for Designing Patient-Specific Cranial Implants Using Rigid ICP Template Alignment and Voxel Space Reconstruction
A semi-automatic software prototype for generating patient-specific cranial implants by aligning healthy skull templates to the damaged target and reconstructing the defect area in voxel space.
Contrastive Learning-based Representation Learning for Computer-Aided Design Models
The proposed ContrastCAD model effectively captures semantic information within the construction sequences of CAD models through contrastive learning. It also introduces a new CAD data augmentation method called Random Replace and Extrude (RRE) to enhance the learning performance of the model.
CADTalk: An Algorithm and Benchmark for Semantic Commenting of CAD Programs
本論文は、CADプログラムの意味的コメントを自動生成するアルゴリズムとベンチマークを提案する。
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