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Weixian Xu is an undergraduate student in the ACM Honors Class at Shanghai Jiao Tong University. His research focuses on machine learning and the development of self-improving AI systems. He has served as a student researcher at the Stanford SALT Lab with Professor Diyi Yang. Previously, he worked in the GAIR Lab at Shanghai Jiao Tong University with Professor Pengfei Liu and collaborated with researchers at Princeton University and AI2.
Xu has co-authored arXiv preprints including ASI-Evolve: AI Accelerates AI (2026) and EEVEE: Towards Test-time Prompt Learning in the Real World for Self-Improving Agents (2026). He also contributed to AlphaGo Moment for Model Architecture Discovery (2025). His work explores recursive self-improvement in AI, test-time prompt learning for agents, and autonomous neural architecture discovery.
Explore Shanghai Jiao Tong University's ASI-Evolve, a self-improving AI framework mimicking human trial-and-error to outperform humans in architecture design, data curation, and algorithms—accelerating breakthroughs in Chinese higher education.
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