IA-RAG: Interval-Algebra-Driven Temporal Reasoning for Dynamic Knowledge Retrieval 事件

IA-RAG: Interval-Algebra-Driven Temporal Reasoning for Dynamic Knowledge Retrieval arXiv:2606.06044v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has shown strong effectiveness in grounding Large Language Models (LLMs) with external knowledge. However, existing RAG and Graph RAG frameworks largely treat knowledge as static or associate time with coarse-grained timestamps or metadata, failing to capture rich temporal structures such as duration, overlap, and containment. We