GenAI Content Detection Task 3: Cross-Domain Machine-Generated Text Detection Challenge

L Dugan, A Zhu, F Alam, P Nakov, M Apidianaki… - arxiv preprint arxiv …, 2025 - arxiv.org
Recently there have been many shared tasks targeting the detection of generated text from
Large Language Models (LLMs). However, these shared tasks tend to focus either on cases …

Are AI Detectors Good Enough? A Survey on Quality of Datasets With Machine-Generated Texts

G Gritsai, A Voznyuk, A Grabovoy… - arxiv preprint arxiv …, 2024 - arxiv.org
The rapid development of autoregressive Large Language Models (LLMs) has significantly
improved the quality of generated texts, necessitating reliable machine-generated text …

Evaluation of LLM Vulnerabilities to Being Misused for Personalized Disinformation Generation

A Zugecova, D Macko, I Srba, R Moro, J Kopal… - arxiv preprint arxiv …, 2024 - arxiv.org
The capabilities of recent large language models (LLMs) to generate high-quality content
indistinguishable by humans from human-written texts rises many concerns regarding their …

LuxVeri at GenAI Detection Task 1: Inverse Perplexity Weighted Ensemble for Robust Detection of AI-Generated Text across English and Multilingual Contexts

MK Mobin, MS Islam - arxiv preprint arxiv:2501.11914, 2025 - arxiv.org
This paper presents a system developed for Task 1 of the COLING 2025 Workshop on
Detecting AI-Generated Content, focusing on the binary classification of machine-generated …

Advacheck at GenAI Detection Task 1: AI Detection Powered by Domain-Aware Multi-Tasking

G Gritsai, A Voznyuk, I Khabutdinov… - arxiv preprint arxiv …, 2024 - arxiv.org
The paper describes a system designed by Advacheck team to recognise machine-
generated and human-written texts in the monolingual subtask of GenAI Detection Task 1 …

[PDF][PDF] CIC-NLP at GenAI Detection Task 1: Advancing Multilingual Machine-Generated Text Detection

G Sidorov, O Kolesnikova - GenAIDetect 2025, 2025 - aclanthology.org
Abstract Machine-written texts are gradually becoming indistinguishable from human-
generated texts, leading to the need to use sophisticated methods to detect them. Team CIC …

CIC-NLP at GenAI Detection Task 1: Advancing Multilingual Machine-Generated Text Detection

TO Abiola, TA Bizuneh, F Uroosa… - Proceedings of the …, 2025 - aclanthology.org
Abstract Machine-written texts are gradually becoming indistinguishable from human-
generated texts, leading to the need to use sophisticated methods to detect them. Team CIC …

AAIG at GenAI Detection Task 1: Exploring Syntactically-Aware, Resource-Efficient Small Autoregressive Decoders for AI Content Detection

A Bhandarkar, R Wilson… - Proceedings of the …, 2025 - aclanthology.org
This paper presents a lightweight and efficient approach to AI-generated content detection
using small autoregressive fine-tuned decoders (AFDs) for secure, on-device deployment …

OSINT at GenAI Detection Task 1: Multilingual MGT Detection: Leveraging Cross-Lingual Adaptation for Robust LLMs Text Identification

S Agrahari, SR Singh - Proceedings of the 1stWorkshop on GenAI …, 2025 - aclanthology.org
Detecting AI-generated text has become in-creasingly prominent. This paper presents our
solution for the DAIGenC Task 1 Subtask 2, where we address the challenge of distin …

TurQUaz at GenAI Detection Task 1: Dr. Perplexity or: How I Learned to Stop Worrying and Love the Finetuning

KE Keleş, M Kutlu - Proceedings of the 1stWorkshop on GenAI …, 2025 - aclanthology.org
This paper details our methods for addressing Task 1 of the GenAI Content Detection shared
tasks, which focus on distinguishing AI-generated text from human-written content. The task …