Retrieval-augmented generation for large language models: A survey

Y Gao, Y Xiong, X Gao, K Jia, J Pan, Y Bi, Y Dai… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …

Large language models for generative information extraction: A survey

D Xu, W Chen, W Peng, C Zhang, T Xu, X Zhao… - Frontiers of Computer …, 2024 - Springer
Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …

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 …

Towards open-world recommendation with knowledge augmentation from large language models

Y Xi, W Liu, J Lin, X Cai, H Zhu, J Zhu, B Chen… - Proceedings of the 18th …, 2024 - dl.acm.org
Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …

Graph retrieval-augmented generation: A survey

B Peng, Y Zhu, Y Liu, X Bo, H Shi, C Hong… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in
addressing the challenges of Large Language Models (LLMs) without necessitating …

How can recommender systems benefit from large language models: A survey

J Lin, X Dai, Y Xi, W Liu, B Chen, H Zhang, Y Liu… - arXiv preprint arXiv …, 2023 - arxiv.org
With the rapid development of online services, recommender systems (RS) have become
increasingly indispensable for mitigating information overload. Despite remarkable …

Enhancing question answering for enterprise knowledge bases using large language models

F Jiang, C Qin, K Yao, C Fang, F Zhuang, H Zhu… - … on Database Systems …, 2024 - Springer
Efficient knowledge management plays a pivotal role in augmenting both the operational
efficiency and the innovative capacity of businesses and organizations. By indexing …

Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation

P Shu, J Chen, Z Liu, H Wang, Z Wu, T Zhong… - arXiv preprint arXiv …, 2024 - arxiv.org
Large Language Models (LLMs) have demonstrated remarkable success across a wide
range of tasks and domains. However, their performance in low-resource language …

All roads lead to rome: Unveiling the trajectory of recommender systems across the llm era

B Chen, X Dai, H Guo, W Guo, W Liu, Y Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
Recommender systems (RS) are vital for managing information overload and delivering
personalized content, responding to users' diverse information needs. The emergence of …

Modular rag: Transforming rag systems into lego-like reconfigurable frameworks

Y Gao, Y Xiong, M Wang, H Wang - arXiv preprint arXiv:2407.21059, 2024 - arxiv.org
Retrieval-augmented Generation (RAG) has markedly enhanced the capabilities of Large
Language Models (LLMs) in tackling knowledge-intensive tasks. The increasing demands of …