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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 45 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 24
Collections
Discover the best community collections!
Collections including paper arxiv:2506.05176
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Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
Paper • 2506.07044 • Published • 112 -
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning
Paper • 2506.09513 • Published • 99 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 98 -
Seedance 1.0: Exploring the Boundaries of Video Generation Models
Paper • 2506.09113 • Published • 102
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DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 418 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 141 -
StoryMaker: Towards Holistic Consistent Characters in Text-to-image Generation
Paper • 2409.12576 • Published • 16 -
Transformer Explainer: Interactive Learning of Text-Generative Models
Paper • 2408.04619 • Published • 171
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 58 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 44 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
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GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
Paper • 2508.06471 • Published • 176 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 234 -
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Paper • 2507.06261 • Published • 60 -
SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment
Paper • 2507.20984 • Published • 56
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Reinforcement Pre-Training
Paper • 2506.08007 • Published • 260 -
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
Paper • 2506.06395 • Published • 130 -
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
Paper • 2506.05176 • Published • 71 -
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 271
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Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
Paper • 2506.05176 • Published • 71 -
Advancing Multimodal Reasoning: From Optimized Cold Start to Staged Reinforcement Learning
Paper • 2506.04207 • Published • 47 -
MiMo-VL Technical Report
Paper • 2506.03569 • Published • 79 -
UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
Paper • 2506.03147 • Published • 58
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 35 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 28 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 127 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 23
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Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 83 -
Piccolo2: General Text Embedding with Multi-task Hybrid Loss Training
Paper • 2405.06932 • Published • 21 -
Gecko: Versatile Text Embeddings Distilled from Large Language Models
Paper • 2403.20327 • Published • 49 -
Multilingual E5 Text Embeddings: A Technical Report
Paper • 2402.05672 • Published • 23
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 45 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 24
-
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
Paper • 2508.06471 • Published • 176 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 234 -
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Paper • 2507.06261 • Published • 60 -
SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment
Paper • 2507.20984 • Published • 56
-
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
Paper • 2506.07044 • Published • 112 -
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning
Paper • 2506.09513 • Published • 99 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 98 -
Seedance 1.0: Exploring the Boundaries of Video Generation Models
Paper • 2506.09113 • Published • 102
-
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 260 -
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
Paper • 2506.06395 • Published • 130 -
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
Paper • 2506.05176 • Published • 71 -
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 271
-
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 418 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 141 -
StoryMaker: Towards Holistic Consistent Characters in Text-to-image Generation
Paper • 2409.12576 • Published • 16 -
Transformer Explainer: Interactive Learning of Text-Generative Models
Paper • 2408.04619 • Published • 171
-
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
Paper • 2506.05176 • Published • 71 -
Advancing Multimodal Reasoning: From Optimized Cold Start to Staged Reinforcement Learning
Paper • 2506.04207 • Published • 47 -
MiMo-VL Technical Report
Paper • 2506.03569 • Published • 79 -
UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
Paper • 2506.03147 • Published • 58
-
LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 35 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 28 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 127 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 23
-
LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 58 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 44 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
-
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 83 -
Piccolo2: General Text Embedding with Multi-task Hybrid Loss Training
Paper • 2405.06932 • Published • 21 -
Gecko: Versatile Text Embeddings Distilled from Large Language Models
Paper • 2403.20327 • Published • 49 -
Multilingual E5 Text Embeddings: A Technical Report
Paper • 2402.05672 • Published • 23