Collections
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Collections including paper arxiv:2410.07073
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Qwen2.5-Coder Technical Report
Paper • 2409.12186 • Published • 123 -
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
Paper • 2409.12122 • Published • 1 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 13 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 67
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LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 51 -
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Paper • 2408.08872 • Published • 97 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 114 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 50
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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 • 53 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 30
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MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 124 -
Evolutionary Optimization of Model Merging Recipes
Paper • 2403.13187 • Published • 49 -
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
Paper • 2402.03766 • Published • 12 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 64
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Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters
Paper • 2403.02677 • Published • 16 -
Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
Paper • 2403.03003 • Published • 9 -
InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding
Paper • 2403.01487 • Published • 15 -
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks
Paper • 2403.00522 • Published • 44
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
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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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 79 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 142 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25