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Yu-Kai Wu

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Preprint Sep 2026

Breaking the Environment Wall: A Unified Framework for Preparing and Evolving Agent-Native Environments

Env-Rethink is proposed, a system with 27B post-trained model that supports three main capabilities that adaptively builds Collection Maps and Event Logs to supplement necessary context and evolves environments through virtual event histories that alter environmental states and evidence relationships.

Yu-Kai Wu, Yuan-Jing Yang, Leon Zhou et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Breaking the Environment Wall: Evolving LLM Agent Environments for Recursive Self-Improvement

Env-Rethink is proposed, a system with 27B post-trained model that supports three main capabilities that adaptively builds Collection Maps and Event Logs to supplement necessary context and evolves environments through virtual event histories that alter environmental states and evidence relationships.

Yu-Kai Wu, Yuan-Jing Yang, Leon Zhou et al. · 0 citations
Aug 2026

MoDora: A Multimodal Document AI Assistant Harness

MoDora is presented, an interactive, tree-structured multimodal document analysis agent harness designed to make the document analysis process transparent and controllable, and introduces an end-to-end user experience through three core functionalities.

Yu-Kai Wu, Bang-Rui Xu, Shao-Lin Yu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement

This work uses the Headroom-Closed Index (HCI) to reveal the problems of existing LLMs, and introduces the RSI concept and its development roadmap: from improvement-execution autonomy, improvement-strategy autonomy, experience-acquisition autonomy, and environment-adaptation autonomy, to recursive meta-improvement.

Yi-Xiang Duan, Ying Liu, Zi-Rui Tang et al. · 10 citations · ⚡3

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