mlsanityData to 14 Oct 2026

A Language and Its Dimensions: Intrinsic Dimensions of Language Fractal Structures

arXiv 2311.10217 ↗First posted 16 Nov 2023cs.CL cs.AI math.ATcited by 4

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Abstract (arXiv)

The present paper introduces a novel object of study - a language fractal structure. We hypothesize that a set of embeddings of all n-grams of a natural language constitutes a representative sample of this fractal set. (We use the term Hailonakea to refer to the sum total of all language fractal structures, over all n). The paper estimates intrinsic (genuine) dimensions of language fractal structures for the Russian and English languages. To this end, we employ methods based on (1) topological data analysis and (2) a minimum spanning tree of a data graph for a cloud of points considered (Steele theorem). For both languages, for all n, the intrinsic dimensions appear to be non-integer values (typical for fractal sets), close to 9 for both of the Russian and English language.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 5 of its 40 references that are in the map. First posted on arXiv 16 Nov 2023.

Builds on

5 of 40 references.

References · 5

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  4. 2023Intrinsic Dimension Estimation for Robust Detection of AI-Generated Textscited by 112
  5. 2023Multiperiodic Processes: Ergodic Sources with a Sublinear Entropycited by 9

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Citing papers per year: 2024: 1; 2025: 3.

4 papers.