mlsanityData to 7 Oct 2026

Trends and Challenges in Authorship Analysis: A Review of ML, DL, and LLM Approaches

arXiv 2505.15422 ↗First posted 21 May 2025cs.CLcited by 2

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Abstract (arXiv)

Authorship analysis plays an important role in diverse domains, including forensic linguistics, academia, cybersecurity, and digital content authentication. This paper presents a systematic literature review on two key sub-tasks of authorship analysis; Author Attribution and Author Verification. The review explores SOTA methodologies, ranging from traditional ML approaches to DL models and LLMs, highlighting their evolution, strengths, and limitations, based on studies conducted from 2015 to 2024. Key contributions include a comprehensive analysis of methods, techniques, their corresponding feature extraction techniques, datasets used, and emerging challenges in authorship analysis. The study highlights critical research gaps, particularly in low-resource language processing, multilingual adaptation, cross-domain generalization, and AI-generated text detection. This review aims to help researchers by giving an overview of the latest trends and challenges in authorship analysis. It also points out possible areas for future study. The goal is to support the development of better, more reliable, and accurate authorship analysis system in diverse textual domain.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 35 of its 180 references that are in the map. First posted on arXiv 21 May 2025.

Builds on

35 of 180 references.

References · 35

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  10. 2024Can Large Language Models Identify Authorship?cited by 40
  11. 2019Explainable Authorship Verification in Social Media via Attention-based Similarity Learningcited by 36
  12. 2016Understanding Convolutional Neural Networks with A Mathematical Modelcited by 33
23 more
  1. 2024Training-free LLM-generated Text Detection by Mining Token Probability Sequencescited by 33
  2. 2022On the State of the Art in Authorship Attribution and Authorship Verificationcited by 27
  3. 2024Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScorecited by 27
  4. 2023A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Textscited by 23
  5. 2023Who Wrote it and Why? Prompting Large-Language Models for Authorship Verificationcited by 19
  6. 2019Siamese Networks for Large-Scale Author Identificationcited by 12
  7. 2024On the Limitations of Large Language Models (LLMs): False Attributioncited by 12
  8. 2019Assessing the Applicability of Authorship Verification Methodscited by 11
  9. 2023Understanding writing style in social media with a supervised contrastively pre-trained transformercited by 11
  10. 2024Sui Generis: Large Language Models for Authorship Attribution and Verification in Latincited by 8
  11. 2020A Self-supervised Representation Learning of Sentence Structure for Authorship Attributioncited by 6
  12. 2022Cracking Double-Blind Review: Authorship Attribution with Deep Learningcited by 6
  13. 2021Rethinking the Authorship Verification Experimental Setupscited by 5
  14. 2020Authorship Attribution in Bangla literature using Character-level CNNcited by 4
  15. 2022A comparison of several AI techniques for authorship attribution on Romanian textscited by 4
  16. 2023T5 meets Tybalt: Author Attribution in Early Modern English Drama Using Large Language Modelscited by 3
  17. 2024ALMs: Authorial Language Models for Authorship Attributioncited by 3
  18. 2024CAVE: Controllable Authorship Verification Explanationscited by 3
  19. 2024A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attributioncited by 3
  20. 2024Authorship Attribution in Bangla Literature (AABL) via Transfer Learning using ULMFiTcited by 2
  21. 2020A Step Towards Interpretable Authorship Verificationcited by 1
  22. 2023Integrating Bidirectional Long Short-Term Memory with Subword Embedding for Authorship Attributioncited by 1
  23. 2024Towards Effective Authorship Attribution: Integrating Class-Incremental Learningcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025From the Rock Floor to the Cloud: A Systematic Survey of State-of-the-Art NLP in Battery Life Cyclecited by 0
  2. 2026AuthBench: A Large-Scale Multilingual Benchmark for Authorship Representation across Genres and Lengthscited by 0