mlsanityData to 14 Oct 2026

Who Wrote it and Why? Prompting Large-Language Models for Authorship Verification

arXiv 2310.08123 ↗First posted 12 Oct 2023cs.CLcited by 19

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Abstract (arXiv)

Authorship verification (AV) is a fundamental task in natural language processing (NLP) and computational linguistics, with applications in forensic analysis, plagiarism detection, and identification of deceptive content. Existing AV techniques, including traditional stylometric and deep learning approaches, face limitations in terms of data requirements and lack of explainability. To address these limitations, this paper proposes PromptAV, a novel technique that leverages Large-Language Models (LLMs) for AV by providing step-by-step stylometric explanation prompts. PromptAV outperforms state-of-the-art baselines, operates effectively with limited training data, and enhances interpretability through intuitive explanations, showcasing its potential as an effective and interpretable solution for the AV task.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 12 of its 26 references that are in the map. First posted on arXiv 12 Oct 2023.

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12 of 26 references.

References · 12

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  4. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  5. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  6. 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,392
  7. 2022Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspectivecited by 41
  8. 2019Explainable Authorship Verification in Social Media via Attention-based Similarity Learningcited by 37
  9. 2016Character-level and Multi-channel Convolutional Neural Networks for Large-scale Authorship Attributioncited by 21
  10. 2016Learning Stylometric Representations for Authorship Analysiscited by 14
  11. 2015Author Identification using Multi-headed Recurrent Neural Networkscited by 13
  12. 2020A Girl Has A Name: Detecting Authorship Obfuscationcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 11; 2026: 4.

19 papers.

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  1. 2025Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verificationcited by 7
  2. 2024Using Prompts to Guide Large Language Models in Imitating a Real Person's Language Stylecited by 6
  3. 2024InstructAV: Instruction Fine-tuning Large Language Models for Authorship Verificationcited by 4
  4. 2024AIDBench: A benchmark for evaluating the authorship identification capability of large language modelscited by 4
  5. 2025Residualized Similarity for Faithfully Explainable Authorship Verificationcited by 4
  6. 2024CAVE: Controllable Authorship Verification Explanationscited by 3
  7. 2025Trends and Challenges in Authorship Analysis: A Review of ML, DL, and LLM Approachescited by 3
  8. 2025Unraveling Interwoven Roles of Large Language Models in Authorship Privacy: Obfuscation, Mimicking, and Verificationcited by 2
  9. 2025How Well Do LLMs Imitate Human Writing Style?cited by 2
  10. 2025Distilling Closed-Source LLM's Knowledge for Locally Stable and Economic Biomedical Entity Linkingcited by 1
  11. 2025Better Call Claude: Can LLMs Detect Changes of Writing Style?cited by 1
  12. 2025One-shot Style Transfer LLM log-probabilities for Authorship Attribution and Verificationcited by 1
7 more
  1. 2025Cross-Genre Authorship Attribution via LLM-Based Retrieve-and-Rerankcited by 1
  2. 2026De-Anonymization at Scale via Tournament-Style Attributioncited by 1
  3. 2025Stylometry recognizes human and LLM-generated texts in short samplescited by 0
  4. 2025Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuningcited by 0
  5. 2026Interpreting Style Representations via Style-Eliciting Promptscited by 0
  6. 2026Introducing the Privacy-HSD Trade-off: Hate Speech Detection, but not at the Cost of Privacycited by 0
  7. 2026Aggregation-Aware Synthetic Text Generation Against Authorship Re-Identificationcited by 0