10 things I learned from burning myself out with AI coding agents

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...
GitHub

Graph Neural Prompting with Large Language Models

Large language models (LLMs) have shown remarkable generalization capability with exceptional performance in various language modeling tasks. However, they still exhibit inherent limitations in ...
IEEE

NAGphormer+: A Tokenized Graph Transformer With Neighborhood Augmentation for Node Classification in Large Graphs

Abstract: Graph Transformers, emerging as a new architecture for graph representation learning, suffer from the quadratic complexity and can only handle graphs with at most thousands of nodes. To this ...
GitHub

symfony/microsoft-graph-mailer

Register an application in your Microsoft Azure portal, Grant this application the Microsoft Graph Mail.Send permission, Create a secret for that app. # MAILER MAILER ...
IEEE

A Graph Representation Learning Approach for Imbalanced Ship Type Recognition Using AIS Trajectory Data

Abstract: Marine transportation constitutes a vital segment of international trade logistics. Recognizing marine carrier ship types is essential for the governance and efficiency of the marine ...
BBC

Gareth Lewis hosts a special debate program with representation from five parties

Greenland, the world order, rugby, climate and women in politics 4 January 2026 55 minutes Available for 22 days Gareth Lewis hosts a debate looking ahead to the Senedd Election in May with James ...
SciELO

Infeasible paths in the context of data flow based testing criteria: identification, classification and prediction

Infeasible paths constitute a bottleneck for the complete automation of software testing, one of the most expensive activities of software quality assurance. Research efforts have been spent on ...