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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 26 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 43 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22
Collections
Discover the best community collections!
Collections including paper arxiv:2406.16860
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Flowing from Words to Pixels: A Framework for Cross-Modality Evolution
Paper • 2412.15213 • Published • 26 -
No More Adam: Learning Rate Scaling at Initialization is All You Need
Paper • 2412.11768 • Published • 41 -
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Paper • 2412.13663 • Published • 135 -
Autoregressive Video Generation without Vector Quantization
Paper • 2412.14169 • Published • 14
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Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 126 -
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
Paper • 2408.11039 • Published • 59 -
Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming
Paper • 2408.16725 • Published • 53 -
Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
Paper • 2408.15998 • Published • 86
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Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Paper • 2406.16860 • Published • 60 -
PaliGemma: A versatile 3B VLM for transfer
Paper • 2407.07726 • Published • 69 -
E5-V: Universal Embeddings with Multimodal Large Language Models
Paper • 2407.12580 • Published • 40 -
Emu3: Next-Token Prediction is All You Need
Paper • 2409.18869 • Published • 94
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Associative Recurrent Memory Transformer
Paper • 2407.04841 • Published • 35 -
Mixture-of-Agents Enhances Large Language Model Capabilities
Paper • 2406.04692 • Published • 58 -
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Paper • 2405.21060 • Published • 66 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 256
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The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale
Paper • 2406.17557 • Published • 93 -
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Paper • 2406.16860 • Published • 60 -
Arboretum: A Large Multimodal Dataset Enabling AI for Biodiversity
Paper • 2406.17720 • Published • 8 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 97
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Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Paper • 2406.16860 • Published • 60 -
Understanding Alignment in Multimodal LLMs: A Comprehensive Study
Paper • 2407.02477 • Published • 23 -
LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 52 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 126
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VoCo-LLaMA: Towards Vision Compression with Large Language Models
Paper • 2406.12275 • Published • 31 -
TroL: Traversal of Layers for Large Language and Vision Models
Paper • 2406.12246 • Published • 35 -
Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning
Paper • 2406.15334 • Published • 9 -
Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning
Paper • 2406.12742 • Published • 15