Cited by 3Information Retrieval and Search BehaviorTopic ModelingRecommender Systems and Techniques

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Introducing ORKG ASK: An AI-Driven Scholarly Literature Search and Exploration System Taking a Neuro-Symbolic Approach

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Oelen, Allard, Jaradeh, Mohamad Yaser, Auer, Sören·2026·Lecture Notes in Computer Science

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Crossref · 10.1007/978-3-031-97207-2_2

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21 of 21 references verified0 citation errors · 0 not checkable

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  • External stores can be updated immediately without retraining and can maintain explicit provenance and versioning.

    “External stores, by contrast, can be updated immediately without retraining and can maintain explicit provenance and versioning [Oelen et al., 2025, Chinthareddy, 2026].”

    From Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering (2026) · cites this paper as Oelen et al., 2025

    Section 3.1 (p. 4) says new documents can be indexed and added to the vector store without retraining the language model. Section 4.1 (p. 7) describes transparency about the context and settings used to generate results, but the paper does not establish that external stores maintain explicit provenance and versioning. It also says documents can be added easily, not necessarily immediately. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 3

  1. Kusupati, A., et al.: Matryoshka representation learning (2024). https://arxiv.org/abs/2205.13147 · arXiv
  2. Lewis, P., et al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., Lin, H. (eds.) Advances in Neural Information Processing Systems, vol. 33, pp. 9459–9474. Curran Associates, Inc. (2020)
  3. Oelen, A., Jaradeh, M.Y., Auer, S.: ORKG ASK: a neuro-symbolic scholarly search and exploration system. Joint Proceedings of Posters, Demos, Workshops, and Tutorials of the 20th International Conference on Semantic Systems (2024). https://ceur-ws.org/Vol-3759/paper7.pdf

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Metadata

Authors
Oelen, A., Jaradeh, M. Y., & Auer, S.
Affiliations
  • Technische Informationsbibliothek (TIB) (DE)
  • Leibniz University Hannover (DE)
Corresponding author
Oelen, Allard
Venue
Lecture Notes in Computer Science
Published
2025-10-12
Pages
11-25
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W4415081517
Cited by
2
References
13
Citations by year
2026: 2
FWCI
2.29
Type
conference paper
Language
en
Open access
Locations
  • Lecture notes in computer science (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
Keywords
scholarly literature search, neuro-symbolic AI, large language models, retrieval-augmented generation, vector search, knowledge graphs, information retrieval, usability evaluation, Open Research Knowledge Graph

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