@inproceedings{chen-etal-2024-retrieval,
title = "Retrieval-Augmented Knowledge Integration into Language Models: A Survey",
author = {Chen, Yuxuan and
R{\"o}der, Daniel and
Erker, Justus-Jonas and
Hennig, Leonhard and
Thomas, Philippe and
M{\"o}ller, Sebastian and
Roller, Roland},
editor = "Li, Sha and
Li, Manling and
Zhang, Michael JQ and
Choi, Eunsol and
Geva, Mor and
Hase, Peter and
Ji, Heng",
booktitle = "Proceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.knowllm-1.5",
pages = "45--63",
abstract = "This survey analyses how external knowledge can be integrated into language models in the context of retrieval-augmentation.The main goal of this work is to give an overview of: (1) Which external knowledge can be augmented? (2) Given a knowledge source, how to retrieve from it and then integrate the retrieved knowledge? To achieve this, we define and give a mathematical formulation of retrieval-augmented knowledge integration (RAKI). We discuss retrieval and integration techniques separately in detail, for each of the following knowledge formats: knowledge graph, tabular and natural language.",
}
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%0 Conference Proceedings
%T Retrieval-Augmented Knowledge Integration into Language Models: A Survey
%A Chen, Yuxuan
%A Röder, Daniel
%A Erker, Justus-Jonas
%A Hennig, Leonhard
%A Thomas, Philippe
%A Möller, Sebastian
%A Roller, Roland
%Y Li, Sha
%Y Li, Manling
%Y Zhang, Michael JQ
%Y Choi, Eunsol
%Y Geva, Mor
%Y Hase, Peter
%Y Ji, Heng
%S Proceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F chen-etal-2024-retrieval
%X This survey analyses how external knowledge can be integrated into language models in the context of retrieval-augmentation.The main goal of this work is to give an overview of: (1) Which external knowledge can be augmented? (2) Given a knowledge source, how to retrieve from it and then integrate the retrieved knowledge? To achieve this, we define and give a mathematical formulation of retrieval-augmented knowledge integration (RAKI). We discuss retrieval and integration techniques separately in detail, for each of the following knowledge formats: knowledge graph, tabular and natural language.
%U https://aclanthology.org/2024.knowllm-1.5
%P 45-63
Markdown (Informal)
[Retrieval-Augmented Knowledge Integration into Language Models: A Survey](https://aclanthology.org/2024.knowllm-1.5) (Chen et al., KnowLLM-WS 2024)
ACL
- Yuxuan Chen, Daniel Röder, Justus-Jonas Erker, Leonhard Hennig, Philippe Thomas, Sebastian Möller, and Roland Roller. 2024. Retrieval-Augmented Knowledge Integration into Language Models: A Survey. In Proceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024), pages 45–63, Bangkok, Thailand. Association for Computational Linguistics.