# Tortured phrases: A dubious writing style emerging in science. Evidence of critical issues affecting established journals

arXiv: https://arxiv.org/abs/2107.06751 · HTML: https://mlsanity.com/paper/2107.06751/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 41 references that are in the map.
- First posted on arXiv 12 Jul 2021.

## Builds on (most cited first, 6 of 6)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Release Strategies and the Social Impacts of Language Models](https://mlsanity.com/paper/1908.09203/) (2019)
- [The Journal Coverage of Web of Science, Scopus and Dimensions: A Comparative Analysis](https://mlsanity.com/paper/2011.00223/) (2020)
- [Comparing the writing style of real and artificial papers](https://mlsanity.com/paper/1506.05702/) (2015)
- [Detecting a network of hijacked journals by its archive](https://mlsanity.com/paper/2101.01224/) (2021)

## Built on by (most cited first, 17 of 17)

- [AI model GPT-3 (dis)informs us better than humans](https://mlsanity.com/paper/2301.11924/) (2023)
- [When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings](https://mlsanity.com/paper/2407.04503/) (2024)
- [SynSciPass: detecting appropriate uses of scientific text generation](https://mlsanity.com/paper/2209.03742/) (2022)
- [Atomic Reasoning for Scientific Table Claim Verification](https://mlsanity.com/paper/2506.06972/) (2025)
- [No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning](https://mlsanity.com/paper/2303.14443/) (2023)
- [A Multi-Agent Perspective on Modern Information Retrieval](https://mlsanity.com/paper/2502.14796/) (2025)
- [Detecting Generated Scientific Papers using an Ensemble of Transformer Models](https://mlsanity.com/paper/2209.08283/) (2022)
- [Investigating the detection of Tortured Phrases in Scientific Literature](https://mlsanity.com/paper/2210.13024/) (2022)
- [Artificial intelligence technologies to support research assessment: A review](https://mlsanity.com/paper/2212.06574/) (2022)
- [A University Framework for the Responsible use of Generative AI in Research](https://mlsanity.com/paper/2404.19244/) (2024)
- [Papilusion at DAGPap24: Paper or Illusion? Detecting AI-generated Scientific Papers](https://mlsanity.com/paper/2407.17629/) (2024)
- [Feature Extraction and Analysis for GPT-Generated Text](https://mlsanity.com/paper/2503.13687/) (2025)
- [Detection of tortured phrases in scientific literature](https://mlsanity.com/paper/2402.03370/) (2024)
- [The EAP-AIAS: Adapting the AI Assessment Scale for English for Academic Purposes](https://mlsanity.com/paper/2408.01075/) (2024)
- [Semantic Reconstruction of Adversarial Plagiarism: A Context-Aware Framework for Detecting and Restoring "Tortured Phrases" in Scientific Literature](https://mlsanity.com/paper/2512.10435/) (2025)
- [Standardization of Post-Publication Code Verification by Journals is Possible with the Support of the Community](https://mlsanity.com/paper/2601.07189/) (2026)
- [The Ghost Couple: Correlated LLM Name Priors and Their Haunting of the Web and Academic Publishing](https://mlsanity.com/paper/2606.02184/) (2026)

## Abstract (arXiv)

Probabilistic text generators have been used to produce fake scientific papers for more than a decade. Such nonsensical papers are easily detected by both human and machine. Now more complex AI-powered generation techniques produce texts indistinguishable from that of humans and the generation of scientific texts from a few keywords has been documented. Our study introduces the concept of tortured phrases: unexpected weird phrases in lieu of established ones, such as 'counterfeit consciousness' instead of 'artificial intelligence.' We combed the literature for tortured phrases and study one reputable journal where these concentrated en masse. Hypothesising the use of advanced language models we ran a detector on the abstracts of recent articles of this journal and on several control sets. The pairwise comparisons reveal a concentration of abstracts flagged as 'synthetic' in the journal. We also highlight irregularities in its operation, such as abrupt changes in editorial timelines. We substantiate our call for investigation by analysing several individual dubious articles, stressing questionable features: tortured writing style, citation of non-existent literature, and unacknowledged image reuse. Surprisingly, some websites offer to rewrite texts for free, generating gobbledegook full of tortured phrases. We believe some authors used rewritten texts to pad their manuscripts. We wish to raise the awareness on publications containing such questionable AI-generated or rewritten texts that passed (poor) peer review. Deception with synthetic texts threatens the integrity of the scientific literature.