Tarek Mahmoud — accepted AI-conference papers

2025

Entity Framing and Role Portrayal in the News

Tarek Mahmoud, Zhuohan Xie, Dimitar Iliyanov Dimitrov, Nikolaos Nikolaidis, Purificação Silvano, Roman Yangarber +6

ACL 2025finding

We introduce a novel multilingual and hierarchical corpus annotated for entity framing and role portrayal in news articles. The dataset uses a unique taxonomy inspired by storytelling elements, comprising 22 fine-grained roles, or archetypes, nested within three main categories: protagonist, antagon…

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2024

LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection

Mervat Abassy, Kareem Elozeiri, Alexander Aziz, Minh Ngoc Ta, Raj Vardhan Tomar, Bimarsha Adhikari +18

EMNLP 2024system demonstrations

The ease of access to large language models (LLMs) has enabled a widespread of machine-generated texts, and now it is often hard to tell whether a piece of text was human-written or machine-generated. This raises concerns about potential misuse, particularly within educational and academic domains.…

Cited by 12 Source ↗PDF ↗code ↗Scholar ↗

2024

M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection

Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun +8

ACL 2024long

The advent of Large Language Models (LLMs) has brought an unprecedented surge in machine-generated text (MGT) across diverse channels. This raises legitimate concerns about its potential misuse and societal implications. The need to identify and differentiate such content from genuine human-generate…

Cited by 41 Source ↗PDF ↗code ↗Scholar ↗