Where do Hallucinations come from?

Sorting algorithms, designed for numerical efficiency, fail when applied to abstract knowledge systems. These failures manifest as hallucinations (false outputs),deviations (incorrect rankings), and systematic distortions. This paper explores the root causes—context blindness, semantic drift, and dataset bias—and quantifies their impact using mathematical models and real-world statistics. A comparative analysis of sorting algorithms reveals their weaknesses in handling complex knowledge. Finally, adaptive solutions are proposed to mitigate these errors and improve coherence in AI-driven systems. To the paper

Apr 14, 2025 - 18:50

Sorting algorithms, designed for numerical efficiency, fail when applied to abstract knowledge systems. These failures manifest as hallucinations (false outputs),deviations (incorrect rankings), and systematic distortions. This paper explores the root causes—context blindness, semantic drift, and dataset bias—and quantifies their impact using mathematical models and real-world statistics. A comparative analysis of sorting algorithms reveals their weaknesses in handling complex knowledge. Finally, adaptive solutions are proposed to mitigate these errors and improve coherence in AI-driven systems.

To the paper