Qinyuan Liu — accepted AI-conference papers

2026

PromptMoE: Generalizable Zero-Shot Anomaly Detection via Visually-Guided Prompt Mixtures

Yuheng Shao, Lizhang Wang, Changhao Li, Peixian Chen, Qinyuan Liu

AAAI 2026technical

Zero-Shot Anomaly Detection (ZSAD) aims to identify and localize anomalous regions in images of unseen object classes. While recent methods based on vision-language models like CLIP show promise, their performance is constrained by existing prompt engineering strategies. Current approaches, whether

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2025

A Risk Prediction Model for Real Estate Corporations Using High-Target Semantic BERT and Improved GRU

Xiaoyan Ma, Peng Zhu, Qinyuan Liu, Zidong Wang

ICASSP 2025accepted

Accurately predicting real estate enterprise risk is crucial for the national economy. Although some initial works have been made on this topic such as Z-score, support vector machines, and logistic regression, there remains a gap in comprehensive models that can effectively capture the dynamic risk…

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