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Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper • 2310.16045 • Published • 17 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper • 2310.14566 • Published • 27 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper • 2310.13355 • Published • 9 -
Conditional Diffusion Distillation
Paper • 2310.01407 • Published • 20
Collections
Discover the best community collections!
Collections including paper arxiv:2308.12966
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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 • 47 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 8 -
LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language Model
Paper • 2404.01331 • Published • 28
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Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper • 2310.16045 • Published • 17 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper • 2310.13355 • Published • 9 -
To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning
Paper • 2311.07574 • Published • 16 -
MyVLM: Personalizing VLMs for User-Specific Queries
Paper • 2403.14599 • Published • 17
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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 • 47 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 8 -
LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language Model
Paper • 2404.01331 • Published • 28
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Visual Instruction Tuning
Paper • 2304.08485 • Published • 16 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 8 -
Improved Baselines with Visual Instruction Tuning
Paper • 2310.03744 • Published • 37 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper • 2310.13355 • Published • 9
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Zero-Shot and Few-Shot Video Question Answering with Multi-Modal Prompts
Paper • 2309.15915 • Published • 2 -
Reformulating Vision-Language Foundation Models and Datasets Towards Universal Multimodal Assistants
Paper • 2310.00653 • Published • 3 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 8 -
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Paper • 2309.09958 • Published • 19
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Qwen Technical Report
Paper • 2309.16609 • Published • 36 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 8 -
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
Paper • 2311.07919 • Published • 10 -
197
Qwen-VL-Plus
📷Chat with images and text using Qwen-VL-Plus
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TinyLLaVA: A Framework of Small-scale Large Multimodal Models
Paper • 2402.14289 • Published • 21 -
ImageBind: One Embedding Space To Bind Them All
Paper • 2305.05665 • Published • 5 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 187 -
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts
Paper • 2206.02770 • Published • 3
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MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer
Paper • 2401.10208 • Published • 1 -
ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities
Paper • 2305.11172 • Published • 1 -
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video
Paper • 2302.00402 • Published -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 8