← Search

Wenkai Zhou

2 accepted papers

2026

OralGPT-Omni: A Versatile Dental Multimodal Large Language Model

CVPR 2026

Multimodal Large Language Models (MLLMs) have exhibited immense potential across numerous medical specialties, yet dentistry remains underexplored, in part due to limited domain-specific data, scarce dental expert annotations, insufficient modality-specific modeling, and challenges in reliability. I

Cited by 0SourceScholar
2025

Bridging Semantic and Modality Gaps in Zero-Shot Captioning via Retrieval from Synthetic Data

EMNLP 2025

Zero-shot image captioning, which aims to generate image descriptions without relying on annotated data, has recently attracted increasing research interest. Pre-trained text-to-image generation models enable the creation of synthetic pairs solely from text data, while existing methods fall short in