Probing the Knowledge Boundary: An Interactive Agentic Framework for Deep Knowledge Extraction 事件

Probing the Knowledge Boundary: An Interactive Agentic Framework for Deep Knowledge Extraction arXiv:2602.00959v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) can be seen as compressed knowledge bases, but it remains unclear what knowledge they truly contain and how far their knowledge boundary extends. Existing benchmarks are mostly static and provide limited support for systematic knowledge probing. In this paper, we propose an interactive agentic framework to systemati