Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT)

Sareem Farooqui; Ali Zain; Dr Muhammad Rafi

Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT)

Sareem Farooqui, Ali Zain, Dr Muhammad Rafi

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Abstract

We participated in two subtasks: Subtask 1, focusing on news articles, and Subtask 2, focusing on academic abstracts. Our submission is based on three distinct architectural approaches: (1) Fine-tuning a RoBERTa-base model, (2) A TF-IDF based system with a Linear Support Vector Machine (SVM) classifier, and (3) An experimental system named Candace, which leverages probabilistic features extracted from multiple Llama-3.2 models (1B and 3B variants) fed into a Transformer Encoder-based classifier. Our RoBERTa-based system demonstrated strong performance on the development and test sets for both subtasks and was chosen as our primary submission to both the shared subtasks.

Anthology ID:: 2025.ranlp-mdaigt.3
Volume:: Proceedings of the Shared Task on Multi-Domain Detection of AI-Generated Text
Month:: September
Year:: 2025
Address:: Varna, Bulgaria
Editors:: Salima Lamsiyah, Saad Ezzini, Abdelkader El Mahdaoui, Hamza Alami, Abdessamad Benlahbib, Samir El Amrani, Salmane Chafik, Hicham Hammouchi
Venues:: RANLP | WS
SIG:
Publisher:: INCOMA Ltd., Shoumen, Bulgaria
Note:
Pages:: 15–19
Language:
URL:: https://aclanthology.org/2025.ranlp-mdaigt.3/
DOI:
Bibkey:
Cite (ACL):: Sareem Farooqui, Ali Zain, and Dr Muhammad Rafi. 2025. Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT). In Proceedings of the Shared Task on Multi-Domain Detection of AI-Generated Text, pages 15–19, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
Cite (Informal):: Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT) (Farooqui et al., RANLP 2025)
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PDF:: https://aclanthology.org/2025.ranlp-mdaigt.3.pdf

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@inproceedings{farooqui-etal-2025-shared,
    title = "Shared Task on Multi-Domain Detection of {AI}-Generated Text ({M}-{DAIGT})",
    author = "Farooqui, Sareem  and
      Zain, Ali  and
      Rafi, Dr Muhammad",
    editor = "Lamsiyah, Salima  and
      Ezzini, Saad  and
      El Mahdaoui, Abdelkader  and
      Alami, Hamza  and
      Benlahbib, Abdessamad  and
      El Amrani, Samir  and
      Chafik, Salmane  and
      Hammouchi, Hicham",
    booktitle = "Proceedings of the Shared Task on Multi-Domain Detection of AI-Generated Text",
    month = sep,
    year = "2025",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://aclanthology.org/2025.ranlp-mdaigt.3/",
    pages = "15--19",
    abstract = "We participated in two subtasks: Subtask 1, focusing on news articles, and Subtask 2, focusing on academic abstracts. Our submission is based on three distinct architectural approaches: (1) Fine-tuning a RoBERTa-base model, (2) A TF-IDF based system with a Linear Support Vector Machine (SVM) classifier, and (3) An experimental system named Candace, which leverages probabilistic features extracted from multiple Llama-3.2 models (1B and 3B variants) fed into a Transformer Encoder-based classifier. Our RoBERTa-based system demonstrated strong performance on the development and test sets for both subtasks and was chosen as our primary submission to both the shared subtasks."
}

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%0 Conference Proceedings
%T Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT)
%A Farooqui, Sareem
%A Zain, Ali
%A Rafi, Dr Muhammad
%Y Lamsiyah, Salima
%Y Ezzini, Saad
%Y El Mahdaoui, Abdelkader
%Y Alami, Hamza
%Y Benlahbib, Abdessamad
%Y El Amrani, Samir
%Y Chafik, Salmane
%Y Hammouchi, Hicham
%S Proceedings of the Shared Task on Multi-Domain Detection of AI-Generated Text
%D 2025
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F farooqui-etal-2025-shared
%X We participated in two subtasks: Subtask 1, focusing on news articles, and Subtask 2, focusing on academic abstracts. Our submission is based on three distinct architectural approaches: (1) Fine-tuning a RoBERTa-base model, (2) A TF-IDF based system with a Linear Support Vector Machine (SVM) classifier, and (3) An experimental system named Candace, which leverages probabilistic features extracted from multiple Llama-3.2 models (1B and 3B variants) fed into a Transformer Encoder-based classifier. Our RoBERTa-based system demonstrated strong performance on the development and test sets for both subtasks and was chosen as our primary submission to both the shared subtasks.
%U https://aclanthology.org/2025.ranlp-mdaigt.3/
%P 15-19

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Markdown (Informal)

[Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT)](https://aclanthology.org/2025.ranlp-mdaigt.3/) (Farooqui et al., RANLP 2025)

Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT) (Farooqui et al., RANLP 2025)

ACL

Sareem Farooqui, Ali Zain, and Dr Muhammad Rafi. 2025. Shared Task on Multi-Domain Detection of AI-Generated Text (M-DAIGT). In Proceedings of the Shared Task on Multi-Domain Detection of AI-Generated Text, pages 15–19, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.