Core Insights - The article discusses the Socratic-Zero framework developed by Alibaba and Shanghai Jiao Tong University, which enables autonomous reasoning training without external data reliance, using only 100 seed questions to generate high-quality, adaptive learning materials [5][14][35] Group 1: Introduction and Background - The current breakthroughs in large language models (LLMs) heavily depend on vast amounts of labeled data, which can lead to inefficiencies in training signals [5] - Socratic-Zero is introduced as a self-evolving training framework that utilizes three intelligent agents: Solver, Teacher, and Generator, to create a dynamic learning environment [9][12] Group 2: Methodology - The Socratic-Zero framework is inspired by Socratic maieutics, emphasizing the importance of high-quality questioning to stimulate self-correction and continuous evolution in AI models [9][12] - The three-agent system operates in a closed-loop self-evolution mechanism, where the Solver's weaknesses drive the Teacher to generate targeted questions, and the Generator learns from the Teacher's strategies to create new problems [13][15] Group 3: Key Innovations - The framework demonstrates significant performance improvements, with the Solver achieving an average accuracy of 56.1% across seven mathematical reasoning benchmarks, a 20.2 percentage point increase compared to previous models [25][32] - The Generator, using only 100 seed questions, produces synthetic data of higher quality than that generated by top closed-source models like GPT-5 and Gemini-2.5-Pro [27][28] Group 4: Experimental Results - The performance of the Solver improved by 15.4 percentage points compared to MetaMath and WizardMath, showcasing the effectiveness of the Socratic-Zero approach [25] - The Generator's question effectiveness reached 95.6%, closely matching GPT-5's performance, indicating the high quality of the generated content [28] Group 5: Engineering and Practicality - Socratic-Zero's training process is designed to be engineering-friendly, ensuring diversity and quality control through multiple validations of seed questions [30][33] - The framework is lightweight and can be implemented with minimal hardware requirements, making it accessible for resource-constrained teams [33][34] Group 6: Future Implications - Socratic-Zero opens a new path for zero-data, self-evolving AI systems, highlighting the potential for intelligent agents to enhance reasoning capabilities without human intervention [35][36]