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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.CV2026

Shared Semantic Codebook Distillation for Unpaired Cross-Modal Medical Classification

Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le +1

The paper introduces Shared Semantic Codebook Distillation, a method that transfers diagnostic knowledge between unpaired medical imaging modalities by representing images with a c…

cs.CV2026

Clinical Graph-Mediated Distillation for Unpaired MRI-to-CFI Hypertension Prediction

Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le +1

Retinal fundus imaging enables low-cost and scalable hypertension (HTN) screening, but HTN-related retinal cues are subtle, yielding high-variance predictions. Brain MRI provides s…

cs.CV2026

Generalized Recognition of Basic Surgical Actions Enables Skill Assessment and Vision-Language-Model-based Surgical Planning

Mengya Xu, Daiyun Shen, Jie Zhang +19

Artificial intelligence, imaging, and large language models have the potential to transform surgical practice, training, and automation. Understanding and modeling of basic surgica…

cs.RO2026

Cosmos-H-Surgical: Learning Surgical Robot Policies from Videos via World Modeling

Yufan He, Pengfei Guo, Mengya Xu +11

Data scarcity remains a fundamental barrier to achieving fully autonomous surgical robots. While large scale vision language action (VLA) models have shown impressive generalizatio…

cs.CV2026

Unsupervised Domain Adaptation with SAM-RefiSeR for Enhanced Brain Tumor Segmentation

Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le +1

Unsupervised Domain Adaptation with SAM-RefiSeR for Enhanced Brain Tumor Segmentation

cs.CV2025

SAP-Bench: Benchmarking Multimodal Large Language Models in Surgical Action Planning

Mengya Xu, Zhongzhen Huang, Dillan Imans +3

Effective evaluation is critical for driving advancements in MLLM research. The surgical action planning (SAP) task, which aims to generate future action sequences from visual inpu…