3 papers
cs.AI2026
Do Language Models Converge to Themselves? Recursive Self-Refinement as Textual Relaxation
Xuening Wu, Qianya Xu, Yanlan Kang +3
Large language models are increasingly used in recursive refinement workflows, where an initial draft is repeatedly revised by the same model. Despite their growing use, the long-t…
cs.HC2026
Human-AI Co-Evolution and Epistemic Collapse: A Dynamical Systems Perspective
Xuening Wu, Yanlan Kang, Qianya Xu +5
Large language models (LLMs) are reshaping how knowledge is produced, with increasing reliance on AI systems for generation, summarization, and reasoning. While prior work has stud…
cs.LG2025
SGM: A Statistical Godel Machine for Risk-Controlled Recursive Self-Modification
Xuening Wu, Shenqin Yin, Yanlan Kang +4
Recursive self-modification is increasingly central in AutoML, neural architecture search, and adaptive optimization, yet no existing framework ensures that such changes are made s…