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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:2404.12390
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BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Paper • 2404.16790 • Published • 7 -
Plot2Code: A Comprehensive Benchmark for Evaluating Multi-modal Large Language Models in Code Generation from Scientific Plots
Paper • 2405.07990 • Published • 16 -
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Paper • 2406.09411 • Published • 18
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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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GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 183 -
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Paper • 2311.16502 • Published • 35 -
BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
RULER: What's the Real Context Size of Your Long-Context Language Models?
Paper • 2404.06654 • Published • 33
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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 • 6 -
LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language Model
Paper • 2404.01331 • Published • 25