mlsanityData to 14 Oct 2026

Can Large Language Models Create New Knowledge for Spatial Reasoning Tasks?

arXiv 2405.14379 ↗First posted 23 May 2024cs.CL cs.AIcited by 1

On the map: LLM reasoning → Spatial and embodied reasoning

Abstract (arXiv)

The potential for Large Language Models (LLMs) to generate new information offers a potential step change for research and innovation. This is challenging to assert as it can be difficult to determine what an LLM has previously seen during training, making "newness" difficult to substantiate. In this paper we observe that LLMs are able to perform sophisticated reasoning on problems with a spatial dimension, that they are unlikely to have previously directly encountered. While not perfect, this points to a significant level of understanding that state-of-the-art LLMs can now achieve, supporting the proposition that LLMs are able to yield significant emergent properties. In particular, Claude 3 is found to perform well in this regard.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Spatial and embodied reasoning, one of 17 directions in LLM reasoning. Builds on 13 of its 25 references that are in the map. First posted on arXiv 23 May 2024.

Builds on

13 of 25 references.

References · 13

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1 more
  1. 2024Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indicationscited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Disentangling generalization and memorization in large language models using chesscited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2025Stuck in the Matrix: Probing Spatial Reasoning in Large Language Models
  2. 2026Do LLMs Build Spatial World Models? Evidence from Grid-World Maze Tasks
  3. 2024Can Large Language Models Reason about the Region Connection Calculus?
  4. 2026From Symbolic to Geometric: Enabling Spatial Reasoning in Large Language Models
  5. 2026Graph-Enhanced Large Language Models for Spatial Search
  6. 2026Do LLMs Build World Models From Text? A Multilingual Diagnostic of Spatial Reasoning
  7. 2025LTD-Bench: Evaluating Large Language Models by Letting Them Draw
  8. 2025Can Large Language Models Integrate Spatial Data? Empirical Insights into Reasoning Strengths and Computational Weaknesses