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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2410.05993
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Towards a Unified View of Preference Learning for Large Language Models: A Survey
Paper • 2409.02795 • Published • 72 -
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct
Paper • 2409.05840 • Published • 49 -
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs
Paper • 2409.05152 • Published • 32 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 140
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MUMU: Bootstrapping Multimodal Image Generation from Text-to-Image Data
Paper • 2406.18790 • Published • 34 -
OmniGen: Unified Image Generation
Paper • 2409.11340 • Published • 115 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51 -
MonoFormer/MonoFormer_ImageNet_256
1B • Updated • 6 • 5
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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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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
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RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 71 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 132 -
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
-
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 129 -
OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents
Paper • 2306.16527 • Published • 46 -
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models
Paper • 2404.12387 • Published • 39 -
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Paper • 2404.16790 • Published • 10
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Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters
Paper • 2403.02677 • Published • 18 -
Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
Paper • 2403.03003 • Published • 11 -
InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding
Paper • 2403.01487 • Published • 16 -
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks
Paper • 2403.00522 • Published • 46
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
Towards a Unified View of Preference Learning for Large Language Models: A Survey
Paper • 2409.02795 • Published • 72 -
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct
Paper • 2409.05840 • Published • 49 -
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs
Paper • 2409.05152 • Published • 32 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 140
-
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
-
MUMU: Bootstrapping Multimodal Image Generation from Text-to-Image Data
Paper • 2406.18790 • Published • 34 -
OmniGen: Unified Image Generation
Paper • 2409.11340 • Published • 115 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51 -
MonoFormer/MonoFormer_ImageNet_256
1B • Updated • 6 • 5
-
RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 71 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 132 -
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
-
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
-
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 129 -
OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents
Paper • 2306.16527 • Published • 46 -
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models
Paper • 2404.12387 • Published • 39 -
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Paper • 2404.16790 • Published • 10
-
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
-
Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters
Paper • 2403.02677 • Published • 18 -
Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
Paper • 2403.03003 • Published • 11 -
InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding
Paper • 2403.01487 • Published • 16 -
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks
Paper • 2403.00522 • Published • 46