Recursively self-improving (RSI) systems are increasingly viewed as a promising means of accelerating progress toward artificial general intelligence. They aim to autonomously improve their capabilities by refining their working pipelines and recursively improving the strategies that guide subsequent refinements, with...
Bang-Rui Xu, Jie Yang, Si-Di Chen et al.· 0 citations
MemTrace is a provenance-aware memory system that preserves execution history and aligns its reuse with the evolving task (e.g., iterative cross-file repair) and repository state and retrieves only what the next action requires.
Hong-Ming Xu, Le Zhou, Zhong-He Jin et al.· 0 citations
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
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
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.· Proceedings of the VLDB Endo...· 0 citations
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.
OmniOpt supplies the research community with an operational coordinate system for selecting optimizers under explicit mechanism and objective assumptions, and charts a direction for the future development of the optimizer community.
Siyuan Li, Jiabao Pan, Yumou Liu et al.· 0 citations
Results show that a fixed-weight, self-evolving harness can revise, recover, and accumulate verified approaches while producing structured trajectories for future supervised and reinforcement learning.
Boxiu Li, Zi-Mo Wen, Yi-Jia Fan et al.· 2 citations· ⚡1
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