--- title: "Who cites Ghostbuster: Detecting Text — 70 citing papers" description: "70 papers of the Elamur Research library cite «Ghostbuster: Detecting Text Ghostwritten by Large Language Models», found in their…" canonical: "https://research.elamur.ai/free/en/papers/verma-2024-ghostbuster-detecting-text-ghostwritten-large/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/verma-2024-ghostbuster-detecting-text-ghostwritten-large/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Ghostbuster: Detecting Text Ghostwritten by Large…](https://md.research.elamur.ai/free/en/papers/verma-2024-ghostbuster-detecting-text-ghostwritten-large/) / cited by # Who cites «Ghostbuster: Detecting Text Ghostwritten by Large Language Models» 70 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Ghostbuster: Detecting Text Ghostwritten by Large Language Models»](https://md.research.elamur.ai/free/en/papers/verma-2024-ghostbuster-detecting-text-ghostwritten-large/) 1. [**Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks arXiv:2306.07899**Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/veselovsky-2023-artificial-artificial-artificial-intelligence-crowd/) **[RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors](https://md.research.elamur.ai/free/en/papers/dugan-2024-raid-shared-benchmark-robust-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liam Dugan, Alyssa Hwang, Filip Trhlík, et al.*2024 · 110 citations* **[Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better](https://md.research.elamur.ai/free/en/papers/liu-2024-does-detectgpt-fully-utilize-perturbation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengchao Liu, Xiaoming Liu, Yichen Wang, et al.*2024 · 16 citations* **[Spotlights and Blindspots: Evaluating Machine-Generated Text Detection](https://md.research.elamur.ai/free/en/papers/stowe-2026-spotlights-blindspots-evaluating-machine-generated/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kevin Stowe, Kailash Patil*2026 · 1 citation* **[Śmigiel Dataset: Laying Foundations for Investigating Machine-Generated Text Detection in Polish](https://md.research.elamur.ai/free/en/papers/strebeyko-2026-smigiel-dataset-laying-foundations-investigating/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jakub Strebeyko, Alina Wróblewska, Piotr Przybyła*2026 · 1 citation* **[GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*2026* **[SearchLLM: Detecting LLM Paraphrased Text by Measuring the Similarity with Regeneration of the Candidate Source via Search Engine](https://md.research.elamur.ai/free/en/papers/son-2026-searchllm-detecting-llm-paraphrased-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hoang-Quoc Nguyen-Son, Minh-Son Dao, Koji Zettsu*2026* 63 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/verma-2024-ghostbuster-detecting-text-ghostwritten-large/) — Ghostbuster: Detecting Text Ghostwritten by Large Language Models