Author

Sikuan Yan

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#machine learning Preprint Sep 2026

Learning Chaos Without Seeing Chaos: Extrapolation of Global Dynamics in Autoregressive Transformers

Autoregressive models are trained to predict a system's behavior one step at a time, and recursive generation allows the learned dynamics to unfold over long horizons. To what extent can such dynamics learned from local observations recover broader organization of an underlying system that was only partially observed d...

Yi-Lun Liu, Yi Zhang, Gan-Yu Wu et al. · 0 citations

Preprint Aug 2026

Mendel G\"odel Machine: Recursive Self-Improving Coding Agents via Comparative Evolution

According to Mendelian principles of controlled inheritance, Mendel G\"odel Machine (MGM) is introduced, which includes two new types of self-modification that better utilizes evidences accumulated and facilitates a faster and better convergence over single-trajectory baselines.

Changzhi Liu, Yilun Liu, Sikuan Yan et al. · 0 citations

Preprint Jul 2026

MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution

MetaSkill-Evolve is introduced, a two-timescale framework that makes agentic skill improvement recursive and outperforms no-skill, static-skill, and single-level evolution baselines on three agentic benchmarks, improving held-out test accuracy over the raw backbone by +23.54, +16.09, and +1.92 points respectively.

Zefeng Wang, Minxi Yan, Jinhe Bi et al. · 4 citations