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#GraphRAG

A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces

Intermediate
Mingxuan Du, Benfeng Xu et al.Feb 3arXiv

A-RAG lets the AI choose how to search, what to read, and when to stop, instead of following a fixed recipe.

#Agentic RAG#Hierarchical Retrieval Interfaces#Keyword Search

WildGraphBench: Benchmarking GraphRAG with Wild-Source Corpora

Beginner
Pengyu Wang, Benfeng Xu et al.Feb 2arXiv

WildGraphBench is a new test that checks how well GraphRAG systems find and combine facts from messy, real-world web pages.

#GraphRAG#Retrieval-Augmented Generation#Wikipedia references

Mindscape-Aware Retrieval Augmented Generation for Improved Long Context Understanding

Intermediate
Yuqing Li, Jiangnan Li et al.Dec 19arXiv

Humans keep a big-picture memory (a “mindscape”) when reading long things; this paper teaches AI to do the same.

#Retrieval-Augmented Generation#Mindscape#Hierarchical Summarization