CompCap: Improving Multimodal Large Language Models with Composite Captions
Paper
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2412.05243
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Published
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18
VLM Papers
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GraPE: A Generate-Plan-Edit Framework for Compositional T2I Synthesis
Paper • 2412.06089 • Published • 4 -
SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation
Paper • 2412.05818 • Published -
FLAIR: VLM with Fine-grained Language-informed Image Representations
Paper • 2412.03561 • Published • 1 -
Active Data Curation Effectively Distills Large-Scale Multimodal Models
Paper • 2411.18674 • Published • 1 -
COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
Paper • 2412.01814 • Published • 1 -
CLIPS: An Enhanced CLIP Framework for Learning with Synthetic Captions
Paper • 2411.16828 • Published • 1 -
FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training
Paper • 2411.11927 • Published • 1 -
LAION-SG: An Enhanced Large-Scale Dataset for Training Complex Image-Text Models with Structural Annotations
Paper • 2412.08580 • Published • 44 -
V2PE: Improving Multimodal Long-Context Capability of Vision-Language Models with Variable Visual Position Encoding
Paper • 2412.09616 • Published • 1 -
InstanceCap: Improving Text-to-Video Generation via Instance-aware Structured Caption
Paper • 2412.09283 • Published • 19 -
jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images
Paper • 2412.08802 • Published • 4 -
ColPali: Efficient Document Retrieval with Vision Language Models
Paper • 2407.01449 • Published • 42