Humanizing methods of AI-generated texts are emerging, which leads to severe performance degradation of current AI text detectors. Most existing detectors are struggling to ensure consistent performance in the huge span from detecting simple AI texts to detecting AI texts humanized in various ways. Targetedly, we propose HiDet, which contains coarse module and subdivision module to give AI texts a double check. We decouple the complete detection process into simple sample detection and difficult sample detection, the coarse module of HiDet filters out simple samples, while hard-to-detect samples like humanized AI texts will be carefully discriminated through the subdivision module which applies a multi-grained contrastive learning strategy. This hierarchical framework makes up for the loophole that humanized AI texts can successfully escape the traditional detector after a single detection, and shows excellent robustness in the task of detecting humanized AI texts. Meanwhile, our framework is flexiable, the subdivision module can be deployed separately on the existing detector as a plug-and-play patch to tremendously improve their performance when facing large-scale humanized AI texts. We hope our work can inspire new sparks in the field of AI-generated text detection.

We introduce RedNote-Vibe, a dataset spanning five years (pre-LLM to July 2025) sourced from lifestyle platform RedNote (Xiaohongshu), capturing the temporal dynamics of content creation and is enriched with comprehensive engagement metrics. To address the detection challenge posed by RedNote-Vibe, we propose the PsychoLinguistic AIGT Detection Framework (PLAD). Grounded in cognitive psychology, PLAD leverages deep psychological signatures for robust and interpretable detection. Our experiments demonstrate PLAD’s superior performance and reveal insights into content dynamics: (1) human content continues to outperform AI in emotionally resonant domains; (2) AI content is more homogeneous and rarely produces breaking posts, however, this human-AI gap narrows for arousing higher-investment interactions; and (3) most interestingly, a small group of users who strategically utilize AI tools can achieve higher engagement outcomes. The dataset is availiable at https://github.com/ydli-ai/RedNote-Vibe.