TwinBI: An Agentic Digital Twin for Efficient Augmented Interactions with Busine

arXiv:2609.03787v1 Announce Type: new Abstract: AI agents increasingly gather evidence, invoke tools, apply constraints, and produce decisions that people or software may commit

arXiv:2604.22748v1 Announce Type: new Abstract: As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment

arXiv:2605.13848v1 Announce Type: new Abstract: Agentic LLM frameworks that rely on prompted orchestration, where the model itself determines workflow transitions, often suffer

arXiv:2605.18770v1 Announce Type: cross Abstract: We present a collaborative agentic GraphRAG framework for expert analysis of commercial registry data. Public registries are