Reproduce “Toward Knowledge-Centric AI: Discovering, Internalizing, and Using Explicit Knowledge Across Agents and Generations” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Yisen Gao, Haoyu Huang, Zhongwei Xie, Yufei Li, Hong Ting Tsang, Boyi Zhang, Qiao Xiao, Tianshi Zheng and 2 more
The authors propose a shared knowledge layer that lets AI agents preserve, process, and revise findings across systems and generations. The layer would align records, abstract reusable lessons while retaining conditions and provenance, and support reasoning with distinct evidence statuses. This position paper identifies internalization as a research priority; it reports no implemented system or measured performance gains.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.