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

arXiv: https://arxiv.org/abs/2310.08123 · HTML: https://mlsanity.com/paper/2310.08123/

## 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.

## Builds on (most cited first, 12 of 12)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [PaLM: Scaling Language Modeling with Pathways](https://mlsanity.com/paper/2204.02311/) (2022)
- [Large Language Models are Zero-Shot Reasoners](https://mlsanity.com/paper/2205.11916/) (2022)
- [Calibrate Before Use: Improving Few-Shot Performance of Language Models](https://mlsanity.com/paper/2102.09690/) (2021)
- [Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective](https://mlsanity.com/paper/2210.10488/) (2022)
- [Explainable Authorship Verification in Social Media via Attention-based Similarity Learning](https://mlsanity.com/paper/1910.08144/) (2019)
- [Character-level and Multi-channel Convolutional Neural Networks for Large-scale Authorship Attribution](https://mlsanity.com/paper/1609.06686/) (2016)
- [Learning Stylometric Representations for Authorship Analysis](https://mlsanity.com/paper/1606.01219/) (2016)
- [Author Identification using Multi-headed Recurrent Neural Networks](https://mlsanity.com/paper/1506.04891/) (2015)
- [A Girl Has A Name: Detecting Authorship Obfuscation](https://mlsanity.com/paper/2005.00702/) (2020)

## Built on by (most cited first, 19 of 19)

- [Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verification](https://mlsanity.com/paper/2503.19099/) (2025)
- [Using Prompts to Guide Large Language Models in Imitating a Real Person's Language Style](https://mlsanity.com/paper/2410.03848/) (2024)
- [InstructAV: Instruction Fine-tuning Large Language Models for Authorship Verification](https://mlsanity.com/paper/2407.12882/) (2024)
- [AIDBench: A benchmark for evaluating the authorship identification capability of large language models](https://mlsanity.com/paper/2411.13226/) (2024)
- [Residualized Similarity for Faithfully Explainable Authorship Verification](https://mlsanity.com/paper/2510.05362/) (2025)
- [CAVE: Controllable Authorship Verification Explanations](https://mlsanity.com/paper/2406.16672/) (2024)
- [Trends and Challenges in Authorship Analysis: A Review of ML, DL, and LLM Approaches](https://mlsanity.com/paper/2505.15422/) (2025)
- [Unraveling Interwoven Roles of Large Language Models in Authorship Privacy: Obfuscation, Mimicking, and Verification](https://mlsanity.com/paper/2505.14195/) (2025)
- [How Well Do LLMs Imitate Human Writing Style?](https://mlsanity.com/paper/2509.24930/) (2025)
- [Distilling Closed-Source LLM's Knowledge for Locally Stable and Economic Biomedical Entity Linking](https://mlsanity.com/paper/2505.19722/) (2025)
- [Better Call Claude: Can LLMs Detect Changes of Writing Style?](https://mlsanity.com/paper/2508.00680/) (2025)
- [One-shot Style Transfer LLM log-probabilities for Authorship Attribution and Verification](https://mlsanity.com/paper/2510.13302/) (2025)
- [Cross-Genre Authorship Attribution via LLM-Based Retrieve-and-Rerank](https://mlsanity.com/paper/2510.16819/) (2025)
- [De-Anonymization at Scale via Tournament-Style Attribution](https://mlsanity.com/paper/2601.12407/) (2026)
- [Stylometry recognizes human and LLM-generated texts in short samples](https://mlsanity.com/paper/2507.00838/) (2025)
- [Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuning](https://mlsanity.com/paper/2512.05747/) (2025)
- [Interpreting Style Representations via Style-Eliciting Prompts](https://mlsanity.com/paper/2606.05716/) (2026)
- [Introducing the Privacy-HSD Trade-off: Hate Speech Detection, but not at the Cost of Privacy](https://mlsanity.com/paper/2608.19006/) (2026)
- [Aggregation-Aware Synthetic Text Generation Against Authorship Re-Identification](https://mlsanity.com/paper/2608.22161/) (2026)

## 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.