Large language models for information retrieval: A survey

Y Zhu, H Yuan, S Wang, J Liu, W Liu, C Deng… - arxiv preprint arxiv …, 2023 - arxiv.org
As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …

Graph of records: Boosting retrieval augmented generation for long-context summarization with graphs

H Zhang, T Feng, J You - arxiv preprint arxiv:2410.11001, 2024 - arxiv.org
Retrieval-augmented generation (RAG) has revitalized Large Language Models (LLMs) by
injecting non-parametric factual knowledge. Compared with long-context LLMs, RAG is …

A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models

Q Zhang, S Chen, Y Bei, Z Yuan, H Zhou… - arxiv preprint arxiv …, 2025 - arxiv.org
Large language models (LLMs) have demonstrated remarkable capabilities in a wide range
of tasks, yet their application to specialized domains remains challenging due to the need for …

HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation

H Liu, Z Wang, X Chen, Z Li, F **ong, Q Yu… - arxiv preprint arxiv …, 2025 - arxiv.org
Retrieval-Augmented Generation (RAG) systems often struggle with imperfect retrieval, as
traditional retrievers focus on lexical or semantic similarity rather than logical relevance. To …

[PDF][PDF] Knowledge Graph and Large Language Model Co-learning via Structure-oriented Retrieval Augmented Generation

C Yang, R Xu, L Luo, S Pan - cs.emory.edu
Recent years have witnessed major technical breakthroughs in AI–facilitated by tremendous
data and high-performance computers, large language models (LLMs) have brought …