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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 11 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 52 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 84 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 30
Collections
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Collections including paper arxiv:2405.17247
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 24 -
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 • 36 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
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RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 65 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 125 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 52 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 84
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 78 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 140 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 177 -
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training
Paper • 2401.00849 • Published • 14 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 42 -
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Paper • 2311.00571 • Published • 40
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An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 84 -
Visual Instruction Tuning
Paper • 2304.08485 • Published • 12 -
Improved Baselines with Visual Instruction Tuning
Paper • 2310.03744 • Published • 36 -
PALO: A Polyglot Large Multimodal Model for 5B People
Paper • 2402.14818 • Published • 23
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What matters when building vision-language models?
Paper • 2405.02246 • Published • 97 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 84 -
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
Paper • 2407.03320 • Published • 92 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 105
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mDPO: Conditional Preference Optimization for Multimodal Large Language Models
Paper • 2406.11839 • Published • 36 -
Pandora: Towards General World Model with Natural Language Actions and Video States
Paper • 2406.09455 • Published • 14 -
WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 14 -
In-Context Editing: Learning Knowledge from Self-Induced Distributions
Paper • 2406.11194 • Published • 15
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Vript: A Video Is Worth Thousands of Words
Paper • 2406.06040 • Published • 22 -
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions
Paper • 2406.04325 • Published • 71 -
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark
Paper • 2406.01574 • Published • 42 -
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Paper • 2405.21075 • Published • 18