Linlin Shen

SKMamba achieves state-of-the-art performance in ZMS maturation assessment by combining structural image analysis with semantic insights from a large language model.

MLLMs still struggle with the spatiotemporal reasoning needed to understand surgical videos, even with chain-of-thought prompting.

MLLMs still struggle to integrate diverse data for clinical reasoning, as evidenced by their poor performance on a new ophthalmology benchmark spanning image quality assessment to diagnosis.

Gaze, often overlooked, reveals deepfake origins with surprising accuracy, enabling a new CLIP-based approach that significantly boosts deepfake attribution and detection.

DINOv3, a vision foundation model trained on general images, surprisingly excels at dental image analysis, especially for the notoriously difficult task of intraoral image understanding.