The field of text analysis and generation is moving towards developing more robust and reliable methods for authenticating and simplifying text. Researchers are focusing on creating innovative watermarking techniques that can detect and prevent tampering with generated text, while also improving the legibility and simplicity of complex characters. One notable direction is the development of model-agnostic detection methods that can preserve text quality while embedding hidden messages. Another area of interest is the simplification of multi-stroke characters, which can facilitate easier learning and communication for non-native speakers. Noteworthy papers include BiMark, which proposes a novel watermarking framework with up to 30% higher extraction rates for short texts, and CoreMark, which introduces a robust and universal text watermarking technique with outstanding generalizability across languages and fonts.