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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 33 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 26 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 123 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
Collections
Discover the best community collections!
Collections including paper arxiv:2411.14794
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Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Paper • 2412.18319 • Published • 37 -
Token-Budget-Aware LLM Reasoning
Paper • 2412.18547 • Published • 45 -
Efficiently Serving LLM Reasoning Programs with Certaindex
Paper • 2412.20993 • Published • 35 -
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Paper • 2412.17256 • Published • 45
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Rethinking Data Selection at Scale: Random Selection is Almost All You Need
Paper • 2410.09335 • Published • 16 -
From Generalist to Specialist: Adapting Vision Language Models via Task-Specific Visual Instruction Tuning
Paper • 2410.06456 • Published • 36 -
Emergent properties with repeated examples
Paper • 2410.07041 • Published • 8 -
Personalized Visual Instruction Tuning
Paper • 2410.07113 • Published • 70
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SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers
Paper • 2407.09413 • Published • 10 -
MAVIS: Mathematical Visual Instruction Tuning
Paper • 2407.08739 • Published • 31 -
Kvasir-VQA: A Text-Image Pair GI Tract Dataset
Paper • 2409.01437 • Published • 71 -
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct
Paper • 2409.05840 • Published • 47
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MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 19 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 15 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 15 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31
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BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 25 -
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Paper • 2404.12803 • Published • 30 -
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
Paper • 2404.13013 • Published • 31 -
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Paper • 2404.06512 • Published • 30