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
January 5, 2024
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December 26, 2023
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December 10, 2023
A Practical Survey on Emerging Threats from AI-driven Voice Attacks: How Vulnerable are Commercial Voice Control Systems?
Yuanda Wang, Qiben Yan, Nikolay Ivanov, Xun Chen
Topological Data Analysis for Neural Network Analysis: A Comprehensive Survey
Rubén Ballester, Carles Casacuberta, Sergio Escalera
A Comprehensive Survey on Multi-modal Conversational Emotion Recognition with Deep Learning
Yuntao Shou, Tao Meng, Wei Ai, Nan Yin, Keqin Li
December 5, 2023
December 1, 2023
November 28, 2023
November 21, 2023
November 20, 2023