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
A Comprehensive Survey with Critical Analysis for Deepfake Speech Detection
Lam Pham, Phat Lam, Tin Nguyen, Hieu Tang, Dat Tran, Alexander Schindler, Taron Zakaryan, Alexander Polonsky, Canh Vu
Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely
Siyun Zhao, Yuqing Yang, Zilong Wang, Zhiyuan He, Luna K. Qiu, Lili Qiu