Showing cs.DBShow all
3 papers · 1 filter
cs.DB2026
EvoRAG: Making Knowledge Graph-based RAG Automatically Evolve through Feedback-driven Backpropagation
Zhenbo Fu, Yuanzhe Zhang, Qiange Wang +5
Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) has emerged as a promising paradigm for enhancing LLM reasoning by retrieving multi-hop paths from KGs. However, exist…
cs.DB2026
Towards Autonomous Graph Data Analytics with Analytics-Augmented Generation
Qiange Wang, Chaoyi Chen, Jingqi Gao +3
This paper argues that reliable end-to-end graph data analytics cannot be achieved by retrieval- or code-generation-centric LLM agents alone. Although large language models (LLMs)…
cs.DB2023
Towards Transaction as a Service
Yanfeng Zhang, Weixing Zhou, Yang Ren +3
This paper argues for decoupling transaction processing from existing two-layer cloud-native databases and making transaction processing as an independent service. By building a tr…