Author

Jing-Nan Zheng

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#artificial intelligence Preprint Oct 2026

Safin-1.5: Safety-Native Architecture and Verifiable Reasoning for Recursive Safety Improvement

Recursive self-improvement (RSI) enables large language models to advance their capabilities through successive updates, but these updates can also introduce new risks and weaken existing safeguards. In line with the AI-45{\deg} Law, we pursue Safety RSI, in which safety develops as an intrinsic capability alongside ge...

Jing-Nan Zheng, Cheng Jin, Ming Zhang et al. · 0 citations

#artificial intelligence Preprint Oct 2026

ReSI: Recursive Safety Improvement toward Resistant and Resilient AI

Recursive self-improvement, the participation of AI systems in improving their own capabilities, is beginning to move from theoretical prospect to practice, posing both challenges and opportunities for safety alignment. Models evolve through frequent updates, and their safety alignment requires continual adaptation to...

Jing-Nan Zheng, Dong-Cheng Zhang, Yi Zhang et al. · 1 citation

#machine learning Preprint Aug 2026

Safin-1: Safety from Within through Memory-Native State Evolution

The routed-state interface unifies contextual memory and persistent capability adaptation within the model's native computation, reframing memory from a passive record of prior context into an active substrate for maintaining and evolving model behavior.

Ming Zhang, Kai-Sen Yang, Shu Yu et al. · 0 citations