---
title: "Who cites M4: Multi-generator, — 88 citing papers"
description: "88 papers of the Elamur Research library cite «M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text…"
canonical: "https://research.elamur.ai/free/en/papers/wang-2023-m4-multi-generator-multi-domain/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2023-m4-multi-generator-multi-domain/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [M4: Multi-generator, Multi-domain, and…](https://md.research.elamur.ai/free/en/papers/wang-2023-m4-multi-generator-multi-domain/) / cited by

# Who cites «M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection»

88 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · [← back to «M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection»](https://md.research.elamur.ai/free/en/papers/wang-2023-m4-multi-generator-multi-domain/)

1. [**Can AI-Generated Text be Reliably Detected? arXiv:2303.11156**Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, et al.*2023 · 306 citations*](https://md.research.elamur.ai/free/en/papers/sadasivan-2023-ai-generated-text-reliably-detected/)
2. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
3. [**Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text arXiv:2401.12070**Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/hans-2024-spotting-llms-binoculars-zero-shot/)
4. **[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*
5. **[Do-Not-Answer: Evaluating Safeguards in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2024-do-not-answer-evaluating-safeguards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxia Wang, Haonan Li, Xudong Han, et al.*2024 · 93 citations*
6. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
7. **[SemEval-2026 Task 13: Detecting Machine-Generated Code with Multiple Programming Languages, Generators, and Application Scenarios](https://md.research.elamur.ai/free/en/papers/orel-2026-semeval-2026-task-13-detecting/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 41 citations*
8. **[The AraGenEval Shared Task on Arabic Authorship Style Transfer and AI Generated Text Detection](https://md.research.elamur.ai/free/en/papers/abudalfa-2025-arageneval-shared-task-arabic-authorship/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Shadi Abudalfa, Saad Ezzini, Ahmed Abdelali, et al.*2025 · 36 citations*
9. **[AICD Bench: A Challenging Benchmark for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/orel-2026-aicd-bench-challenging-benchmark-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 23 citations*
10. **[AbjadGenEval: Abjad AI Generated Text Detection Shared Task for Languages Using Arabic Script at AbjadNLP 2026](https://md.research.elamur.ai/free/en/papers/ezzini-2026-abjadgeneval-abjad-ai-generated-text/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Saad Ezzini, Irfan Ahmad, Salmane Chafik, et al.*2026 · 10 citations*
11. **[FAID: Fine-grained AI-generated Text Detection using Multi-task Auxiliary and Multi-level Contrastive Learning](https://md.research.elamur.ai/free/en/papers/ta-2026-faid-fine-grained-ai-generated/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Minh Ngoc Ta, Dong Cao Van, Duc-Anh Hoang, et al.*2026 · 3 citations*
12. **[Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysis](https://md.research.elamur.ai/free/en/papers/xia-2026-explaining-generalization-ai-generated-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuxi Xia, Kinga Stańczak, Benjamin Roth*2026 · 2 citations*
13. **[DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution](https://md.research.elamur.ai/free/en/papers/teja-2026-damasha-detecting-ai-mixed-adversarial/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**L. D. M. S. Sai Teja, N. Siva Gopala Krishna, Ufaq Khan, et al.*2026 · 1 citation*
14. **[DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection](https://md.research.elamur.ai/free/en/papers/wu-2026-detectrl-x-reliable-multilingual-real/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junchao Wu, Yefeng Liu, Chenyu Zhu, et al.*2026*
15. **[Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI](https://md.research.elamur.ai/free/en/papers/man-2026-explainable-disentangled-representation-learning-generalizable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hieu Man, Van-Cuong Pham, Nghia Trung Ngo, et al.*2026*
16. **[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*
17. **[Reasoning-Aware AIGC Detection via Alignment and Reinforcement](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoning-aware-aigc-detection-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhao Wang, Max Xiong, Jianxun Lian, et al.*2026*
18. **[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*
19. **[What Are LLMs Doing to Scientific Communication? Measuring Changes in Writing Practices and Reading Experience](https://md.research.elamur.ai/free/en/papers/miletic-2026-what-are-llms-doing-scientific/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Filip Miletić, Neele Falk*2026*

69 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/wang-2023-m4-multi-generator-multi-domain/) — M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection
