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A Community-driven vision for a new Knowledge Resource for AI

arXiv 2506.16596 ↗First posted 19 Jun 2025cs.AIcited by 0

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Abstract (arXiv)

The long-standing goal of creating a comprehensive, multi-purpose knowledge resource, reminiscent of the 1984 Cyc project, still persists in AI. Despite the success of knowledge resources like WordNet, ConceptNet, Wolfram|Alpha and other commercial knowledge graphs, verifiable, general-purpose widely available sources of knowledge remain a critical deficiency in AI infrastructure. Large language models struggle due to knowledge gaps; robotic planning lacks necessary world knowledge; and the detection of factually false information relies heavily on human expertise. What kind of knowledge resource is most needed in AI today? How can modern technology shape its development and evaluation? A recent AAAI workshop gathered over 50 researchers to explore these questions. This paper synthesizes our findings and outlines a community-driven vision for a new knowledge infrastructure. In addition to leveraging contemporary advances in knowledge representation and reasoning, one promising idea is to build an open engineering framework to exploit knowledge modules effectively within the context of practical applications. Such a framework should include sets of conventions and social structures that are adopted by contributors.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 89 references that are in the map. First posted on arXiv 19 Jun 2025.

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References · 15

  1. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,065
  2. 2018Constraint Answer Set Programming without Groundingcited by 38
  3. 2024GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answeringcited by 37
  4. 2022The Defeat of the Winograd Schema Challengecited by 25
  5. 2023Dialectical language model evaluation: An initial appraisal of the commonsense spatial reasoning abilities of LLMscited by 20
  6. 2024Reframing Spatial Reasoning Evaluation in Language Models: A Real-World Simulation Benchmark for Qualitative Reasoningcited by 16
  7. 2022FOLD-SE: An Efficient Rule-based Machine Learning Algorithm with Scalable Explainabilitycited by 15
  8. 2022Biolink Model: A Universal Schema for Knowledge Graphs in Clinical, Biomedical, and Translational Sciencecited by 13
  9. 2024HepLean: Digitalising high energy physicscited by 10
  10. 2025LLM+AL: Bridging Large Language Models and Action Languages for Complex Reasoning about Actionscited by 10
  11. 2022Formalizing Chemical Physics using the Lean Theorem Provercited by 9
  12. 2016Modelling Chemical Reasoning to Predict Reactionscited by 8
3 more
  1. 2021Toward a New Science of Common Sensecited by 6
  2. 2015ASPMT(QS): Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theoriescited by 1
  3. 2016Deeply Semantic Inductive Spatio-Temporal Learningcited by 1

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