Promoting responsible and energy conscious artificial intelligence: An enhanced measurement of alternatives and ranking according to compromise solution approach via disc spherical fuzzy Sugeno–Weber Z-aggregation information

Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025

Investigating how experienced developers use agents in building software, including their motivations, strategies, task suitability, and sentiments finds that while experienced developers value agents as a productivity boost, they retain their agency in software design and implementation out of insistence on fundamental software quality attributes.

A systematic review of machine learning techniques to address diagnosis and treatment of autism: challenges and opportunities

This systematic review evaluates 55 studies from 2017 to 2023 on the application of machine learning techniques to ASD, highlighting key challenges and opportunities, particularly the need for models that can integrate complex data to improve diagnostic accuracy and treatment outcomes.

Convergent Evolution: How Different Language Models Learn Similar Number Representations

This paper identifies two different routes through which models can acquire geometrically separable features: they can learn them from complementary co-occurrence signals in general language data, including text-number co-occurrence and cross-number interaction, or from multi-token addition problems.

A Comprehensive Review of Artificial Intelligence Techniques for Power Quality Improvement in Renewable Energy-Based Microgrids: Recent Trends, Challenges, and Future Directions

TabularQGAN: a quantum generative model for tabular data synthesis

A novel quantum generative model for synthesizing tabular data by proposing a quantum generative adversarial network architecture with flexible data encoding and a novel quantum circuit ansatz for effectively modeling tabular data is introduced.

Self-Evolving Agents as Dynamic Graph Transformation: A Survey and New Perspective

This survey model agent state as a dynamic graph, where memories, tools, skills, workflows, and inter-agent relations are represented as typed nodes, edges, and subgraphs updated through schema-constrained rewrites to provide a compact structural lens for designing and governing self-evolving agents.