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LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 52 -
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Paper • 2408.08872 • Published • 100 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 133 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51
Collections
Discover the best community collections!
Collections including paper arxiv:2412.14835
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Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Paper • 2406.16860 • Published • 63 -
Understanding Alignment in Multimodal LLMs: A Comprehensive Study
Paper • 2407.02477 • Published • 24 -
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 • 133
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BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 26 -
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
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 28 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
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Human-like Episodic Memory for Infinite Context LLMs
Paper • 2407.09450 • Published • 62 -
MUSCLE: A Model Update Strategy for Compatible LLM Evolution
Paper • 2407.09435 • Published • 23 -
Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training
Paper • 2407.09121 • Published • 6 -
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
Paper • 2407.14482 • Published • 26
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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34
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MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 129 -
Evolutionary Optimization of Model Merging Recipes
Paper • 2403.13187 • Published • 58 -
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
Paper • 2402.03766 • Published • 15 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 72
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Context Tuning for Retrieval Augmented Generation
Paper • 2312.05708 • Published • 16 -
Dense X Retrieval: What Retrieval Granularity Should We Use?
Paper • 2312.06648 • Published • 1 -
RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Paper • 2401.18059 • Published • 47 -
Retrieval-Augmented Generation for Large Language Models: A Survey
Paper • 2312.10997 • Published • 12
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LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 52 -
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Paper • 2408.08872 • Published • 100 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 133 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51
-
Human-like Episodic Memory for Infinite Context LLMs
Paper • 2407.09450 • Published • 62 -
MUSCLE: A Model Update Strategy for Compatible LLM Evolution
Paper • 2407.09435 • Published • 23 -
Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training
Paper • 2407.09121 • Published • 6 -
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
Paper • 2407.14482 • Published • 26
-
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Paper • 2406.16860 • Published • 63 -
Understanding Alignment in Multimodal LLMs: A Comprehensive Study
Paper • 2407.02477 • Published • 24 -
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 • 133
-
iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34
-
BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 26 -
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
-
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 129 -
Evolutionary Optimization of Model Merging Recipes
Paper • 2403.13187 • Published • 58 -
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
Paper • 2402.03766 • Published • 15 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 72
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 28 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
-
Context Tuning for Retrieval Augmented Generation
Paper • 2312.05708 • Published • 16 -
Dense X Retrieval: What Retrieval Granularity Should We Use?
Paper • 2312.06648 • Published • 1 -
RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Paper • 2401.18059 • Published • 47 -
Retrieval-Augmented Generation for Large Language Models: A Survey
Paper • 2312.10997 • Published • 12