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
December 21, 2022
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November 10, 2022
Computer Vision on X-ray Data in Industrial Production and Security Applications: A Comprehensive Survey
Mehdi Rafiei, Jenni Raitoharju, Alexandros Iosifidis
A Comprehensive Survey on Distributed Training of Graph Neural Networks
Haiyang Lin, Mingyu Yan, Xiaochun Ye, Dongrui Fan, Shirui Pan, Wenguang Chen, Yuan Xie
November 7, 2022
November 5, 2022
October 29, 2022