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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 38 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
Collections
Discover the best community collections!
Collections including paper arxiv:2404.12803
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TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Paper • 2404.12803 • Published • 29 -
OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text
Paper • 2406.08418 • Published • 28 -
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages
Paper • 2406.10118 • Published • 30
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Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation
Paper • 2404.19752 • Published • 22 -
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Paper • 2404.16821 • Published • 53 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 75 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 124
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BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Paper • 2404.12803 • Published • 29 -
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
Paper • 2404.13013 • Published • 30 -
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Paper • 2404.06512 • Published • 29
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Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper • 2310.16045 • Published • 14 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper • 2310.13355 • Published • 6 -
To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning
Paper • 2311.07574 • Published • 14 -
MyVLM: Personalizing VLMs for User-Specific Queries
Paper • 2403.14599 • Published • 15
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Improved Baselines with Visual Instruction Tuning
Paper • 2310.03744 • Published • 37 -
DeepSeek-VL: Towards Real-World Vision-Language Understanding
Paper • 2403.05525 • Published • 39 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 7 -
LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language Model
Paper • 2404.01331 • Published • 25
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Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models
Paper • 2404.07973 • Published • 30 -
RegionGPT: Towards Region Understanding Vision Language Model
Paper • 2403.02330 • Published • 2 -
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Paper • 2404.12803 • Published • 29 -
Pegasus-v1 Technical Report
Paper • 2404.14687 • Published • 30
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CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents
Paper • 2004.12629 • Published • 2 -
LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking
Paper • 2204.08387 • Published • 2 -
Text Role Classification in Scientific Charts Using Multimodal Transformers
Paper • 2402.14579 • Published • 1 -
An inclusive review on deep learning techniques and their scope in handwriting recognition
Paper • 2404.08011 • Published • 1