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pro vyhledávání: '"Raval, Ananya"'
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
The deployment of Large Language Models (LLMs) in diverse applications necessitates an assurance of safety without compromising the contextual integrity of the generated content. Traditional approaches, including safety-specific fine-tuning or advers
Externí odkaz:
http://arxiv.org/abs/2405.11290
Acceleration of graph applications on GPUs has found large interest due to the ubiquitous use of graph processing in various domains. The inherent \textit{irregularity} in graph applications leads to several challenges for parallelization. A key chal
Externí odkaz:
http://arxiv.org/abs/1711.00231