Comprehensive Survey
Comprehensive surveys in various scientific fields systematically review existing research, aiming to synthesize key findings, identify gaps, and guide future directions. Current research focuses on evaluating and improving the trustworthiness, efficiency, and bias mitigation of models across diverse domains, including large language models, image generation, and autonomous systems. These surveys are crucial for advancing understanding within specific subfields and facilitating the development of more robust and reliable technologies with broader practical applications.
Papers
October 28, 2023
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September 28, 2023
Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey
Lea Demelius, Roman Kern, Andreas Trügler
A Comprehensive Survey of Document-level Relation Extraction (2016-2023)
Julien Delaunay, Hanh Thi Hong Tran, Carlos-Emiliano González-Gallardo, Georgeta Bordea, Nicolas Sidere, Antoine Doucet
September 23, 2023
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