PhD student, SUN YAT-SEN UNIVERSITY
1 paper at NeurIPS 2025
We propose MindGYM, a thinking-centric data synthesis framework that injects cognitive traits into QA generation, enabling language and vision-language models to self-synthesize high-quality, low-variance data for efficient fine-tuning.