# SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection

arXiv: https://arxiv.org/abs/2404.14183 · HTML: https://mlsanity.com/paper/2404.14183/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- Builds on 41 of its 86 references that are in the map.
- First posted on arXiv 22 Apr 2024.

## Builds on (most cited first, 30 of 41)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature](https://mlsanity.com/paper/2301.11305/) (2023)
- [Defending Against Neural Fake News](https://mlsanity.com/paper/1905.12616/) (2019)
- [Release Strategies and the Social Impacts of Language Models](https://mlsanity.com/paper/1908.09203/) (2019)
- [GLTR: Statistical Detection and Visualization of Generated Text](https://mlsanity.com/paper/1906.04043/) (2019)
- [How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection](https://mlsanity.com/paper/2301.07597/) (2023)
- [Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense](https://mlsanity.com/paper/2303.13408/) (2023)
- [Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text](https://mlsanity.com/paper/2401.12070/) (2024)
- [Automatic Detection of Generated Text is Easiest when Humans are Fooled](https://mlsanity.com/paper/1911.00650/) (2019)
- [Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models](https://mlsanity.com/paper/2111.02840/) (2021)
- [DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text](https://mlsanity.com/paper/2306.05540/) (2023)
- [Automatic Detection of Machine Generated Text: A Critical Survey](https://mlsanity.com/paper/2011.01314/) (2020)
- [M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection](https://mlsanity.com/paper/2305.14902/) (2023)
- [TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation](https://mlsanity.com/paper/2109.13296/) (2021)
- [Sparks: Inspiration for Science Writing using Language Models](https://mlsanity.com/paper/2110.07640/) (2021)
- [OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples](https://mlsanity.com/paper/2307.11729/) (2023)
- [RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting](https://mlsanity.com/paper/2305.15685/) (2023)
- [Real or Fake Text?: Investigating Human Ability to Detect Boundaries Between Human-Written and Machine-Generated Text](https://mlsanity.com/paper/2212.12672/) (2022)
- [Stylometric Detection of AI-Generated Text in Twitter Timelines](https://mlsanity.com/paper/2303.03697/) (2023)
- [The Next Chapter: A Study of Large Language Models in Storytelling](https://mlsanity.com/paper/2301.09790/) (2023)
- [M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection](https://mlsanity.com/paper/2402.11175/) (2024)
- [Neural Deepfake Detection with Factual Structure of Text](https://mlsanity.com/paper/2010.07475/) (2020)
- [Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective](https://mlsanity.com/paper/2210.10488/) (2022)
- [GPT-who: An Information Density-based Machine-Generated Text Detector](https://mlsanity.com/paper/2310.06202/) (2023)
- [Few-Shot Detection of Machine-Generated Text using Style Representations](https://mlsanity.com/paper/2401.06712/) (2024)
- [CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learning](https://mlsanity.com/paper/2212.10341/) (2022)
- [Adversarial Robustness of Neural-Statistical Features in Detection of Generative Transformers](https://mlsanity.com/paper/2203.07983/) (2022)
- [Authorship Obfuscation in Multilingual Machine-Generated Text Detection](https://mlsanity.com/paper/2401.07867/) (2024)
- [Team QUST at SemEval-2024 Task 8: A Comprehensive Study of Monolingual and Multilingual Approaches for Detecting AI-generated Text](https://mlsanity.com/paper/2402.11934/) (2024)

## Built on by (most cited first, 30 of 30)

- [DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning](https://mlsanity.com/paper/2410.20964/) (2024)
- [Beemo: Benchmark of Expert-edited Machine-generated Outputs](https://mlsanity.com/paper/2411.04032/) (2024)
- [LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection](https://mlsanity.com/paper/2408.04284/) (2024)
- [Robust AI-Generated Text Detection by Restricted Embeddings](https://mlsanity.com/paper/2410.08113/) (2024)
- [Machine-generated text detection prevents language model collapse](https://mlsanity.com/paper/2502.15654/) (2025)
- [GenAI Content Detection Task 1: English and Multilingual Machine-Generated Text Detection: AI vs. Human](https://mlsanity.com/paper/2501.11012/) (2025)
- [Characterizing LLM-driven Social Network: The Chirper.ai Case](https://mlsanity.com/paper/2504.10286/) (2025)
- [Stress-testing Machine Generated Text Detection: Shifting Language Models Writing Style to Fool Detectors](https://mlsanity.com/paper/2505.24523/) (2025)
- [Increasing the Robustness of the Fine-tuned Multilingual Machine-Generated Text Detectors](https://mlsanity.com/paper/2503.15128/) (2025)
- [Human Texts Are Outliers: Detecting LLM-generated Texts via Out-of-distribution Detection](https://mlsanity.com/paper/2510.08602/) (2025)
- [Detection of Human and Machine-Authored Fake News in Urdu](https://mlsanity.com/paper/2410.19517/) (2024)
- [GenAI Content Detection Task 3: Cross-Domain Machine-Generated Text Detection Challenge](https://mlsanity.com/paper/2501.08913/) (2025)
- [GenAI Content Detection Task 2: AI vs. Human -- Academic Essay Authenticity Challenge](https://mlsanity.com/paper/2412.18274/) (2024)
- [Robust and Fine-Grained Detection of AI Generated Texts](https://mlsanity.com/paper/2504.11952/) (2025)
- [Transformer and Hybrid Deep Learning Based Models for Machine-Generated Text Detection](https://mlsanity.com/paper/2405.17964/) (2024)
- [Sharif-MGTD at SemEval-2024 Task 8: A Transformer-Based Approach to Detect Machine Generated Text](https://mlsanity.com/paper/2407.11774/) (2024)
- [RKadiyala at SemEval-2024 Task 8: Black-Box Word-Level Text Boundary Detection in Partially Machine Generated Texts](https://mlsanity.com/paper/2410.16659/) (2024)
- [LuxVeri at GenAI Detection Task 1: Inverse Perplexity Weighted Ensemble for Robust Detection of AI-Generated Text across English and Multilingual Contexts](https://mlsanity.com/paper/2501.11914/) (2025)
- [LuxVeri at GenAI Detection Task 3: Cross-Domain Detection of AI-Generated Text Using Inverse Perplexity-Weighted Ensemble of Fine-Tuned Transformer Models](https://mlsanity.com/paper/2501.11918/) (2025)
- [LLMTrace: A Corpus for Classification and Fine-Grained Localization of AI-Written Text](https://mlsanity.com/paper/2509.21269/) (2025)
- [Why AI-Generated Text Detection Fails: Evidence from Explainable AI Beyond Benchmark Accuracy](https://mlsanity.com/paper/2603.23146/) (2026)
- [Beyond speculation: Measuring the growing presence of LLM-generated texts in multilingual disinformation](https://mlsanity.com/paper/2503.23242/) (2025)
- [Domain Gating Ensemble Networks for AI-Generated Text Detection](https://mlsanity.com/paper/2505.13855/) (2025)
- [AINL-Eval 2025 Shared Task: Detection of AI-Generated Scientific Abstracts in Russian](https://mlsanity.com/paper/2508.09622/) (2025)
- [Automatic Machine Translation Detection Using a Surrogate Multilingual Translation Model](https://mlsanity.com/paper/2511.02958/) (2025)
- [LLM Output Detectability and Task Performance Can be Jointly Optimized](https://mlsanity.com/paper/2605.01350/) (2026)
- [AEyeDE: An Attention-Based Attribution Framework for AI-Generated Text Detection](https://mlsanity.com/paper/2606.00016/) (2026)
- [Detecting LLM-Generated Tokens in Human--LLM Coauthored Text](https://mlsanity.com/paper/2607.21458/) (2026)
- [Build it, Break it, Repeat: Benchmarking and improving LLM-manipulated disinformation detection in social media posts](https://mlsanity.com/paper/2608.09510/) (2026)
- [Policy-Conditioned AI-Use Detection: An Evidentiary Framework for Academic Publishing](https://mlsanity.com/paper/2609.38427/) (2026)

## Abstract (arXiv)

We present the results and the main findings of SemEval-2024 Task 8: Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection. The task featured three subtasks. Subtask A is a binary classification task determining whether a text is written by a human or generated by a machine. This subtask has two tracks: a monolingual track focused solely on English texts and a multilingual track. Subtask B is to detect the exact source of a text, discerning whether it is written by a human or generated by a specific LLM. Subtask C aims to identify the changing point within a text, at which the authorship transitions from human to machine. The task attracted a large number of participants: subtask A monolingual (126), subtask A multilingual (59), subtask B (70), and subtask C (30). In this paper, we present the task, analyze the results, and discuss the system submissions and the methods they used. For all subtasks, the best systems used LLMs.