6 papers
Fundus Image-based Glaucoma Screening via Retinal Knowledge-Oriented Dynamic Multi-Level Feature Integration
Yuzhuo Zhou, Chi Liu, Sheng Shen +9
While deep learning has advanced automated glaucoma screening via color fundus photography, existing purely data-driven models often overfit to confounding imaging artifacts and st…
Are LLMs Ready for Computer Science Education? A Cross-Domain, Cross-Lingual and Cognitive-Level Evaluation Using Professional Certification Exams
Chen Gao, Chi Liu, Zhengquan Luo +10
Large language models (LLMs) are increasingly applied in computer science education for tasks such as tutoring, content generation, and code assessment. However, systematic evaluat…
Robust AI-Synthesized Image Detection via Multi-feature Frequency-aware Learning
Hongfei Cai, Chi Liu, Sheng Shen +2
The rapid progression of generative AI (GenAI) technologies has heightened concerns regarding the misuse of AI-generated imagery. To address this issue, robust detection methods ha…
Enhancing Fundus Image-based Glaucoma Screening via Dynamic Global-Local Feature Integration
Yuzhuo Zhou, Chi Liu, Sheng Shen +4
With the advancements in medical artificial intelligence (AI), fundus image classifiers are increasingly being applied to assist in ophthalmic diagnosis. While existing classificat…
Unleashing the Power of Pre-trained Encoders for Universal Adversarial Attack Detection
Yinghe Zhang, Chi Liu, Shuai Zhou +2
Adversarial attacks pose a critical security threat to real-world AI systems by injecting human-imperceptible perturbations into benign samples to induce misclassification in deep…
Can LLMs Assist Computer Education? an Empirical Case Study of DeepSeek
Dongfu Xiao, Chen Gao, Zhengquan Luo +2
This study presents an empirical case study to assess the efficacy and reliability of DeepSeek-V3, an emerging large language model, within the context of computer education. The e…