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arXiv:2507.07505cs.CL

Hallucination Stations: On Some Basic Limitations of Transformer-Based Language Models

Varin Sikka, Vishal Sikka

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

In this paper we explore hallucinations and related capability limitations in LLMs and LLM-based agents from the perspective of computational complexity. We show that beyond a certain complexity, LLMs are incapable of carrying out computational and agentic tasks or verifying their accuracy.

arXiv comments
6 pages; to be submitted to AAAI-26 after reviews
Journal reference
DOI
Subjects
cs.CLComputation and Language cs.AIArtificial Intelligence

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Feb 2026 to Feb 2026. Found in 3 HN submissions from Jan 2026 to Jan 2026. Open submission discussions.

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  1. Why I don't think AGI is imminent 1 comment

    • Thanks for reading, and I really appreciate your comments! > who feed their produced tokens back as inputs, and whose tuning effectively rewards it for doing this skillfully Ah, this is a great point, and not something that I considered. I agree that the token feedback does…

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