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pro vyhledávání: '"Rahman, Mizanur"'
Autor:
Raza, Shaina, Rahman, Mizanur, Kamawal, Safiullah, Toroghi, Armin, Raval, Ananya, Navah, Farshad, Kazemeini, Amirmohammad
Recommender Systems (RS) play an integral role in enhancing user experiences by providing personalized item suggestions. This survey reviews the progress in RS inclusively from 2017 to 2024, effectively connecting theoretical advances with practical
Externí odkaz:
http://arxiv.org/abs/2407.13699
Autor:
Laskar, Md Tahmid Rahman, Alqahtani, Sawsan, Bari, M Saiful, Rahman, Mizanur, Khan, Mohammad Abdullah Matin, Khan, Haidar, Jahan, Israt, Bhuiyan, Amran, Tan, Chee Wei, Parvez, Md Rizwan, Hoque, Enamul, Joty, Shafiq, Huang, Jimmy
Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them in real-w
Externí odkaz:
http://arxiv.org/abs/2407.04069
Recent improvements in large language models (LLMs) have significantly enhanced natural language processing (NLP) applications. However, these models can also inherit and perpetuate biases from their training data. Addressing this issue is crucial, y
Externí odkaz:
http://arxiv.org/abs/2406.04220
Recommender systems play a pivotal role in helping users navigate an overwhelming selection of products and services. On online platforms, users have the opportunity to share feedback in various modes, including numerical ratings, textual reviews, an
Externí odkaz:
http://arxiv.org/abs/2405.05562
Autor:
Raza, Shaina, Khan, Tahniat, Chatrath, Veronica, Paulen-Patterson, Drai, Rahman, Mizanur, Bamgbose, Oluwanifemi
In today's technologically driven world, the rapid spread of fake news, particularly during critical events like elections, poses a growing threat to the integrity of information. To tackle this challenge head-on, we introduce FakeWatch, a comprehens
Externí odkaz:
http://arxiv.org/abs/2403.09858
Autor:
Deng, Hsien-Wen, Salek, M Sabbir, Rahman, Mizanur, Chowdhury, Mashrur, Shue, Mitch, Apon, Amy W.
In this study, we developed a real-time connected vehicle (CV) speed advisory application that uses public cloud services and tested it on a simulated signalized corridor for different roadway traffic conditions. First, we developed a scalable server
Externí odkaz:
http://arxiv.org/abs/2401.16545
Autonomous vehicles (AVs) rely on the Global Positioning System (GPS) or Global Navigation Satellite Systems (GNSS) for precise (Positioning, Navigation, and Timing) PNT solutions. However, the vulnerability of GPS signals to intentional and unintend
Externí odkaz:
http://arxiv.org/abs/2401.01394
In this paper, we validate the performance of the a sensor fusion-based Global Navigation Satellite System (GNSS) spoofing attack detection framework for Autonomous Vehicles (AVs). To collect data, a vehicle equipped with a GNSS receiver, along with
Externí odkaz:
http://arxiv.org/abs/2401.01304
Despite increasing awareness and research around fake news, there is still a significant need for datasets that specifically target racial slurs and biases within North American political speeches. This is particulary important in the context of upco
Externí odkaz:
http://arxiv.org/abs/2312.03750
In today's technologically driven world, the spread of fake news, particularly during crucial events such as elections, presents an increasing challenge to the integrity of information. To address this challenge, we introduce FakeWatch ElectionShield
Externí odkaz:
http://arxiv.org/abs/2312.03730