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Maram Hasanain

9 accepted papers

2025

Annotating the Annotators: Analysis, Insights and Modelling from an Annotation Campaign on Persuasion Techniques Detection

Davide Bassi, Dimitar Iliyanov Dimitrov, Bernardo D’Auria, Firoj Alam, Maram Hasanain, Christian Moro +4
ACL 2025finding

Persuasion (or propaganda) techniques detection is a relatively novel task in Natural Language Processing (NLP). While there have already been a number of annotation campaigns, they have been based on heuristic guidelines, which have never been thoroughly discussed. Here, we present the first system…

Cited by 4Source ↗PDF ↗Scholar ↗
2025

AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs

Basel Mousi, Nadir Durrani, Fatema Ahmad, Md. Arid Hasan, Maram Hasanain, Tameem Kabbani +3
COLING 2025main

Arabic, with its rich diversity of dialects, remains significantly underrepresented in Large Language Models, particularly in dialectal variations. We address this gap by introducing seven synthetic datasets in dialects alongside Modern Standard Arabic (MSA), created using Machine Translation (MT) c…

Cited by 7Source ↗PDF ↗Scholar ↗
2025

LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content

Mohamed Bayan Kmainasi, Ali Ezzat Shahroor, Maram Hasanain, Sahinur Rahman Laskar, Naeemul Hassan, Firoj Alam
NAACL 2025findings

Large Language Models (LLMs) have demonstrated remarkable success as general-purpose task solvers across various fields. However, their capabilities remain limited when addressing domain-specific problems, particularly in downstream NLP tasks. Research has shown that models fine-tuned on instruction…

Cited by 3Source ↗PDF ↗Scholar ↗
2025

NativQA: Multilingual Culturally-Aligned Natural Query for LLMs

Md. Arid Hasan, Maram Hasanain, Fatema Ahmad, Sahinur Rahman Laskar, Sunaya Upadhyay, Vrunda N Sukhadia +3
ACL 2025finding

Natural Question Answering (QA) datasets play a crucial role in evaluating the capabilities of large language models (LLMs), ensuring their effectiveness in real-world applications. Despite the numerous QA datasets that have been developed and some work done in parallel, there is a notable lack of a…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

PropXplain: Can LLMs Enable Explainable Propaganda Detection?

Maram Hasanain, Md Arid Hasan, Mohamed Bayan Kmainasi, Elisa Sartori, Ali Ezzat Shahroor, Giovanni Da San Martino +1
EMNLP 2025

There has been significant research on propagandistic content detection across different modalities and languages. However, most studies have primarily focused on detection, with little attention given to explanations justifying the predicted label. This is largely due to the lack of resources that

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2024

ArMeme: Propagandistic Content in Arabic Memes

Firoj Alam, Abul Hasnat, Fatema Ahmad, Md. Arid Hasan, Maram Hasanain
EMNLP 2024main

With the rise of digital communication memes have become a significant medium for cultural and political expression that is often used to mislead audience. Identification of such misleading and persuasive multimodal content become more important among various stakeholders, including social media pla…

Cited by 10Source ↗PDF ↗code ↗Scholar ↗
2024

Can GPT-4 Identify Propaganda? Annotation and Detection of Propaganda Spans in News Articles

Maram Hasanain, Fatema Ahmad, Firoj Alam
COLING 2024main

The use of propaganda has spiked on mainstream and social media, aiming to manipulate or mislead users. While efforts to automatically detect propaganda techniques in textual, visual, or multimodal content have increased, most of them primarily focus on English content. The majority of the recent in…

Cited by 27Source ↗PDF ↗Scholar ↗
2021

Automated Fact-Checking for Assisting Human Fact-Checkers

Preslav Nakov, David Corney, Maram Hasanain, Firoj Alam, Tamer Elsayed, Alberto Barrón-Cedeño +3
IJCAI 2021poster

The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism. Nowadays, politicians and other key players enjoy direct access to their audiences through social media, bypassing the filters of official cable…

Cited by 281Source ↗PDF ↗Scholar ↗