Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs Paper • 2504.17432 • Published 3 days ago • 32
RWKV-CLIP: A Robust Vision-Language Representation Learner Paper • 2406.06973 • Published Jun 11, 2024 • 1
CLIP-CID: Efficient CLIP Distillation via Cluster-Instance Discrimination Paper • 2408.09441 • Published Aug 18, 2024 • 2
Croc: Pretraining Large Multimodal Models with Cross-Modal Comprehension Paper • 2410.14332 • Published Oct 18, 2024 • 1
ORID: Organ-Regional Information Driven Framework for Radiology Report Generation Paper • 2411.13025 • Published Nov 20, 2024 • 2
RealSyn: An Effective and Scalable Multimodal Interleaved Document Transformation Paradigm Paper • 2502.12513 • Published Feb 18 • 16
Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs Paper • 2504.17432 • Published 3 days ago • 32
Decoupled Global-Local Alignment for Improving Compositional Understanding Paper • 2504.16801 • Published 3 days ago • 14
UniME Collection UniME is a series of multimodal large language models trained for learning universal multimodal embedding. • 3 items • Updated 2 days ago • 3
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models Paper • 2504.10479 • Published 12 days ago • 242
RealSyn: An Effective and Scalable Multimodal Interleaved Document Transformation Paradigm Paper • 2502.12513 • Published Feb 18 • 16