GitHub

A Dataset and code of Graph Representation of 3D CAD Models for Machining Feature Recognition With Deep Learning

Paper: Graph Representation of 3D CAD Models for Machining Feature Recognition With Deep Learning The MFCAD (Machining Feature CAD) dataset is a comprehensive collection of 3D CAD models with labeled ...
IEEE

Gen-GraphEx: Generative In-Distribution Graph Explanations for Time-Efficient Model-Level Interpretability of GNNs

Abstract: Graph neural networks (GNNs) have become the prevailing methodology for addressing graph data-related tasks, permeating critical domains like recommendation systems and drug development. The ...
AlphaGalileo

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design. In addition, Nature has recently ...
IEEE

Consistent Graph Model Generation with Large Language Models

Abstract: Graph model generation from natural language requirements is an essential task in software engineering, for which large language models (LLMs) have become increasingly popular. A key ...
GitHub

CGBridge: Bridging Code Graphs and Large Language Models for Better Structure-Aware Code Understanding

CGBridge is a novel framework designed to enhance the code understanding capabilities of Large Language Models (LLMs) by integrating rich structural information from code graphs. Our approach follows ...