mlsanityData to 14 Oct 2026

Comparing LLM-generated and human-authored news text using formal syntactic theory

arXiv 2506.01407 ↗First posted 2 Jun 2025cs.CLcited by 11

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Abstract (arXiv)

This study provides the first comprehensive comparison of New York Times-style text generated by six large language models against real, human-authored NYT writing. The comparison is based on a formal syntactic theory. We use Head-driven Phrase Structure Grammar (HPSG) to analyze the grammatical structure of the texts. We then investigate and illustrate the differences in the distributions of HPSG grammar types, revealing systematic distinctions between human and LLM-generated writing. These findings contribute to a deeper understanding of the syntactic behavior of LLMs as well as humans, within the NYT genre.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 9 of its 38 references that are in the map. First posted on arXiv 2 Jun 2025.

Builds on

9 of 38 references.

References · 9

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2023The Falcon Series of Open Language Modelscited by 535
  3. 2023Contrasting Linguistic Patterns in Human and LLM-Generated News Textcited by 62
  4. 2024Do LLMs write like humans? Variation in grammatical and rhetorical stylescited by 62
  5. 2024Detection and Measurement of Syntactic Templates in Generated Textcited by 44
  6. 2017Robust Incremental Neural Semantic Graph Parsingcited by 13
  7. 2024A Linguistic Comparison between Human and ChatGPT-Generated Conversationscited by 9
  8. 2023Explaining Code Examples in Introductory Programming Courses: LLM vs Humanscited by 3
  9. 2025Does a Large Language Model Really Speak in Human-Like Language?cited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 9.

11 papers.

  1. 2026More Aligned, Less Diverse? Analyzing the Grammar and Lexicon of Two Generations of LLMscited by 3
  2. 2025Word Overuse and Alignment in Large Language Models: The Influence of Learning from Human Feedbackcited by 2
  3. 2026AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writingcited by 2
  4. 2025Surprisal reveals diversity gaps in image captioning and different scorers change the storycited by 0
  5. 2026Learn-To-Learn on Arbitrary Textual Conditioning: A Hypernetwork-Driven Meta-Gated LLMcited by 0
  6. 2026What Are LLMs Doing to Scientific Communication? Measuring Changes in Writing Practices and Reading Experiencecited by 0
  7. 2026How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Frameworkcited by 0
  8. 2026Fully Automated Identification of Lexical Alignment and Preference-Stage Shifts in Large Language Modelscited by 0
  9. 2026Detecting undisclosed LLM-generated content in parliamentary textscited by 0
  10. 2026Detecting and Guiding LLM-Generated Korean Poetry with Interpretable Form-level Featurescited by 0
  11. 2026Synthetic Data Characterization via Training Dynamicscited by 0