Zobrazeno 1 - 10
of 2 123
pro vyhledávání: '"IKRAM, MUHAMMAD"'
Autor:
Salman, Muhammad, Zhao, Benjamin Zi Hao, Asghar, Hassan Jameel, Ikram, Muhammad, Kaushik, Sidharth, Kaafar, Mohamed Ali
Adversarial examples add imperceptible alterations to inputs with the objective to induce misclassification in machine learning models. They have been demonstrated to pose significant challenges in domains like image classification, with results show
Externí odkaz:
http://arxiv.org/abs/2408.02310
Autor:
Qayyum, Hina, Ikram, Muhammad, Zhao, Benjamin, Wood, Ian, Kaafar, Mohamad Ali, Kourtellis, Nicolas
Toxic sentiment analysis on Twitter (X) often focuses on specific topics and events such as politics and elections. Datasets of toxic users in such research are typically gathered through lexicon-based techniques, providing only a cross-sectional vie
Externí odkaz:
http://arxiv.org/abs/2406.02801
OpenAI's ChatGPT initiated a wave of technical iterations in the space of Large Language Models (LLMs) by demonstrating the capability and disruptive power of LLMs. OpenAI has prompted large organizations to respond with their own advancements and mo
Externí odkaz:
http://arxiv.org/abs/2405.10547
Autor:
Akhtar, Mohammad Majid, Bhuiyan, Navid Shadman, Masood, Rahat, Ikram, Muhammad, Kanhere, Salil S.
The detection of automated accounts, also known as "social bots", has been an increasingly important concern for online social networks (OSNs). While several methods have been proposed for detecting social bots, significant research gaps remain. Firs
Externí odkaz:
http://arxiv.org/abs/2402.03740
Autor:
Qayyum, Hina, Ikram, Muhammad, Zhao, Benjamin Zi Hao, Wood, an D., Kourtellis, Nicolas, Kaafar, Mohamed Ali
Publikováno v:
2023 IEEE International Conference on Big Data (BigData)
The argument for persistent social media influence campaigns, often funded by malicious entities, is gaining traction. These entities utilize instrumented profiles to disseminate divisive content and disinformation, shaping public perception. Despite
Externí odkaz:
http://arxiv.org/abs/2401.14252
Autor:
Qayyum, Hina, Ikram, Muhammad, Zhao, Benjamin Zi Hao, Wood, Ian D., Kourtellis, Nicolas, Kaafar, Mohamed Ali
In the pursuit of bolstering user safety, social media platforms deploy active moderation strategies, including content removal and user suspension. These measures target users engaged in discussions marked by hate speech or toxicity, often linked to
Externí odkaz:
http://arxiv.org/abs/2401.14141
False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulations
The rapid spread of false information and persistent manipulation attacks on online social networks (OSNs), often for political, ideological, or financial gain, has affected the openness of OSNs. While researchers from various disciplines have invest
Externí odkaz:
http://arxiv.org/abs/2308.12497