The field of reconfigurable intelligent surfaces (RISs) is rapidly advancing, with a focus on overcoming key challenges such as severe double-pathloss and complex multi-user scheduling. Researchers are exploring innovative solutions, including neural channel knowledge maps, impedance-based RIS modeling, and advanced beamforming techniques. These developments have the potential to significantly enhance the performance of next-generation wireless networks. Noteworthy papers include:

• Neural Channel Knowledge Map Assisted Scheduling Optimization of Active IRSs in Multi-User Systems, which proposes a novel scheduling framework based on neural channel knowledge maps.
• Fluid Reconfigurable Intelligent Surface with Element-Level Pattern Reconfigurability: Beamforming and Pattern Co-Design, which introduces a pattern-reconfigurable fluid RIS framework that provides significant advantages in modulating transmission signals.
• Space-time Coded Differential Modulation for Reconfigurable Intelligent Surfaces, which presents a differential space-time modulation scheme that bypasses the requirement for channel state information in RIS systems.