Chinese University of Hong Kong, Shenzhen

Protein-text foundation model placing amino acid sequences and natural language in one token space for protein understanding and de novo design.

Protein dynamics model that samples conformational ensembles autoregressively at slow and fast timescales, generalizing zero-shot to unseen proteins.

Open medical multimodal LLMs (7B and 34B) for visual question answering over radiology, pathology, and endoscopy images, trained on PubMedVision.

Medical vision-language pretraining unifying fusion-encoder and dual-encoder designs, handling image-only, text-only, and paired inputs in one model.

Medical vision-language pretraining framework that injects structured medical knowledge into radiology image-text learning for VQA and retrieval.

Self-supervised medical vision-and-language pretraining via multi-modal masked autoencoders that reconstruct masked image patches and text tokens.