mlsanityData to 7 Oct 2026

Grounding from an AI and Cognitive Science Lens

arXiv 2402.13290 ↗First posted 19 Feb 2024cs.AIcited by 6

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Abstract (arXiv)

Grounding is a challenging problem, requiring a formal definition and different levels of abstraction. This article explores grounding from both cognitive science and machine learning perspectives. It identifies the subtleties of grounding, its significance for collaborative agents, and similarities and differences in grounding approaches in both communities. The article examines the potential of neuro-symbolic approaches tailored for grounding tasks, showcasing how they can more comprehensively address grounding. Finally, we discuss areas for further exploration and development in grounding.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 2 of its 18 references that are in the map. First posted on arXiv 19 Feb 2024.

Builds on

2 of 18 references.

References · 2

  1. 2019The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervisioncited by 369
  2. 2021Grounding 'Grounding' in NLPcited by 44

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 2.

6 papers.