Yufeng Shen

APR-Net: a lightweight multi-scale attention network for oral disease detection

Abstract Multiclass object detection in oral images is important for oral disease screening and computer-aided assessment. Existing lightweight detection models still suffer from insufficient recognition of fine-grained lesions, weak feature representation of low-contrast patholo...

Unsupervised discovery of functional sequence patterns from protein language model with MotifAE

Protein language models (pLMs) learn sequence patterns at evolutionary scale, but these patterns remain inaccessible within these “black box” models. To discover them, we developed MotifAE, an unsupervised framework based on the sparse autoencoder (SAE) architecture that projects...