mlsanityData to 14 Oct 2026

Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions

arXiv 2501.06699 ↗First posted 12 Jan 2025cs.AI cs.IR cs.SCcited by 8

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Abstract (arXiv)

Much has been discussed about how Large Language Models, Knowledge Graphs and Search Engines can be combined in a synergistic manner. A dimension largely absent from current academic discourse is the user perspective. In particular, there remain many open questions regarding how best to address the diverse information needs of users, incorporating varying facets and levels of difficulty. This paper introduces a taxonomy of user information needs, which guides us to study the pros, cons and possible synergies of Large Language Models, Knowledge Graphs and Search Engines. From this study, we derive a roadmap for future research.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 24 of its 64 references that are in the map. First posted on arXiv 12 Jan 2025.

Builds on

24 of 64 references.

References · 24

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  12. 2020Knowledge Graphscited by 621
12 more
  1. 2022Large Language Models Struggle to Learn Long-Tail Knowledgecited by 458
  2. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  3. 2023FreshLLMs: Refreshing Large Language Models with Search Engine Augmentationcited by 318
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  5. 2023From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inferencecited by 170
  6. 2022Deep Bidirectional Language-Knowledge Graph Pretrainingcited by 156
  7. 2023Don't Trust ChatGPT when Your Question is not in English: A Study of Multilingual Abilities and Types of LLMscited by 104
  8. 2023Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modelingcited by 56
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  11. 2023Evaluating the Knowledge Base Completion Potential of GPTcited by 9
  12. 2023Language Models sounds the Death Knell of Knowledge Graphscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 6; 2026: 2.

8 papers.