mlsanityData to 14 Oct 2026

Why Cannot Large Language Models Ever Make True Correct Reasoning?

arXiv 2508.10265 ↗First posted 14 Aug 2025cs.AI cs.LOcited by 1

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

Recently, with the application progress of AIGC tools based on large language models (LLMs), led by ChatGPT, many AI experts and more non-professionals are trumpeting the "reasoning ability" of the LLMs. The present author considers that the so-called "reasoning ability" of LLMs are just illusions of those people who with vague concepts. In fact, the LLMs can never have the true reasoning ability. This paper intents to explain that, because the essential limitations of their working principle, the LLMs can never have the ability of true correct reasoning.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 2 of its 15 references that are in the map. First posted on arXiv 14 Aug 2025.

Builds on

2 of 15 references.

References · 2

  1. 2023A Comprehensive Overview of Large Language Modelscited by 648
  2. 2022Talking About Large Language Modelscited by 175

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Citing papers per year: 2025: 1.

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  6. 2024Can Large Language Models Act as Symbolic Reasoners?
  7. 2025Large Language Models' Reasoning Stalls: An Investigation into the Capabilities of Frontier Models
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