The trifluoromethylthiolated group (SCF3) is characterized by its strong electron‐withdrawing ability, excellent lipophilicity, good stability, and bioavailability, making it highly relevant for applications in drug design and development. This review summarizes recent advances in CX (H, Cl, OTf, B(OH)2) trifluoromethylthiolation reaction from 2014 to 2024. The discussion is organized into three major sections: 1) transition metal‐catalyzed CH trifluoromethylthiolation reactions facilitated by directing groups, 2) transition metal‐catalyzed trifluoromethylthiolation via cross‐coupling reactions, and 3) light‐assisted transition metal‐catalyzed trifluoromethylthiolation reactions. Additionally, this review examines the substrate scope, limitations, and partial mechanisms associated with these transformations.

ABSTRACTThe increasingly complex modern communication environment poses challenges for automatic modulation recognition (AMR) techniques. In AMR tasks, in order to more comprehensively capture signal features and improve recognition performance, we propose a model named Multiscale Mobile Inverted Bottleneck Convolution and Manhattan Self‐Attention Network (3M‐Net). In this 3M‐Net, the MSMB block is designed to extract multiscale local features of the signals, and the MMG block is designed to enhance global information modeling of the model. Then, a hierarchical backbone that contains the two blocks is designed to extract multilevel features. Extensive experiments on the RML2016.10a and RML2018.01a datasets demonstrate that the 3M‐Net model achieves superior recognition performance.