mlsanityData to 7 Oct 2026

TextDescriptives: A Python package for calculating a large variety of metrics from text

arXiv 2301.02057 ↗First posted 5 Jan 2023cs.CLcited by 13

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Abstract (arXiv)

TextDescriptives is a Python package for calculating a large variety of metrics from text. It is built on top of spaCy and can be easily integrated into existing workflows. The package has already been used for analysing the linguistic stability of clinical texts, creating features for predicting neuropsychiatric conditions, and analysing linguistic goals of primary school students. This paper describes the package and its features.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 2 of its 15 references that are in the map. First posted on arXiv 5 Jan 2023.

Builds on

2 of 15 references.

References · 2

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  2. 2021Scaling Language Models: Methods, Analysis & Insights from Training Gophercited by 1,199

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 6; 2025: 5; 2026: 1.

13 papers.

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  1. 2024Beemo: Benchmark of Expert-edited Machine-generated Outputscited by 26
  2. 2025A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Educationcited by 11
  3. 2024LLM See, LLM Do: Guiding Data Generation to Target Non-Differentiable Objectivescited by 6
  4. 2024Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progresscited by 6
  5. 2025Alignment Drift in CEFR-prompted LLMs for Interactive Spanish Tutoringcited by 6
  6. 2023Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddingscited by 5
  7. 2024MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviewscited by 5
  8. 2025A Lightweight Approach to Detection of AI-Generated Texts Using Stylometric Featurescited by 4
  9. 2025DACTYL: Diverse Adversarial Corpus of Texts Yielded from Large Language Modelscited by 3
  10. 2024Which LLMs are Difficult to Detect? A Detailed Analysis of Potential Factors Contributing to Difficulties in LLM Text Detectioncited by 2
  11. 2025Facilitating Cognitive Accessibility with LLMs: A Multi-Task Approach to Easy-to-Read Text Generationcited by 2
  12. 2024Mining Reasons For And Against Vaccination From Unstructured Data Using Nichesourcing and AI Data Augmentationcited by 1
1 more
  1. 2026Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training Debiasingcited by 0