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Collections including paper arxiv:2505.18129

about 18 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 13
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 255
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60
Magistral

Paper • 2506.10910 • Published Jun 12 • 63

One-RL-to-See-Them-All

One RL to See Them All: Visual Triple Unified Reinforcement Learning. GitHub: https://github.com/MiniMax-AI/One-RL-to-See-Them-All

One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60
One-RL-to-See-Them-All/Orsta-Data-47k

Updated Jun 4 • 423 • 15
One-RL-to-See-Them-All/Orsta-7B

Image-Text-to-Text • 8B • Updated Jun 4 • 1.45k • 10
One-RL-to-See-Them-All/Orsta-32B-0321

Image-Text-to-Text • 33B • Updated May 26 • 6

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 596 • 95
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 35
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 89

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Paper • 2505.09568 • Published May 14 • 97
Qwen3 Technical Report

Paper • 2505.09388 • Published May 14 • 276
GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning

Paper • 2505.11049 • Published May 16 • 61
Emerging Properties in Unified Multimodal Pretraining

Paper • 2505.14683 • Published May 20 • 133

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 31
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 5

One-RL-to-See-Them-All

https://github.com/MiniMax-AI/One-RL-to-See-Them-All

One-RL-to-See-Them-All/Orsta-7B

Image-Text-to-Text • 8B • Updated Jun 4 • 1.45k • 10
One-RL-to-See-Them-All/Orsta-32B-0321

Image-Text-to-Text • 33B • Updated May 26 • 6
One-RL-to-See-Them-All/Orsta-32B-0326

Image-Text-to-Text • 33B • Updated Jun 4 • 11 • 5
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60

One-RL-to-See-Them-All

https://github.com/MiniMax-AI/One-RL-to-See-Them-All

One-RL-to-See-Them-All/Orsta-7B

Image-Text-to-Text • 8B • Updated Jun 4 • 1.45k • 10
One-RL-to-See-Them-All/Orsta-32B-0321

Image-Text-to-Text • 33B • Updated May 26 • 6
One-RL-to-See-Them-All/Orsta-32B-0326

Image-Text-to-Text • 33B • Updated Jun 4 • 11 • 5
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60

Scaling Law for Quantization-Aware Training

Paper • 2505.14302 • Published May 20 • 76
Reward Reasoning Model

Paper • 2505.14674 • Published May 20 • 37
Qwen3 Technical Report

Paper • 2505.09388 • Published May 14 • 276
AdaptThink: Reasoning Models Can Learn When to Think

Paper • 2505.13417 • Published May 19 • 82

Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities

Paper • 2505.02567 • Published May 5 • 79
TabSTAR: A Foundation Tabular Model With Semantically Target-Aware Representations

Paper • 2505.18125 • Published May 23 • 113
Distilling LLM Agent into Small Models with Retrieval and Code Tools

Paper • 2505.17612 • Published May 23 • 81
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60

about 18 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 13
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 31
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 5

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 255
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60
Magistral

Paper • 2506.10910 • Published Jun 12 • 63

One-RL-to-See-Them-All

https://github.com/MiniMax-AI/One-RL-to-See-Them-All

One-RL-to-See-Them-All/Orsta-7B

Image-Text-to-Text • 8B • Updated Jun 4 • 1.45k • 10
One-RL-to-See-Them-All/Orsta-32B-0321

Image-Text-to-Text • 33B • Updated May 26 • 6
One-RL-to-See-Them-All/Orsta-32B-0326

Image-Text-to-Text • 33B • Updated Jun 4 • 11 • 5
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60

One-RL-to-See-Them-All

One RL to See Them All: Visual Triple Unified Reinforcement Learning. GitHub: https://github.com/MiniMax-AI/One-RL-to-See-Them-All

One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60
One-RL-to-See-Them-All/Orsta-Data-47k

Updated Jun 4 • 423 • 15
One-RL-to-See-Them-All/Orsta-7B

Image-Text-to-Text • 8B • Updated Jun 4 • 1.45k • 10
One-RL-to-See-Them-All/Orsta-32B-0321

Image-Text-to-Text • 33B • Updated May 26 • 6

One-RL-to-See-Them-All

https://github.com/MiniMax-AI/One-RL-to-See-Them-All

One-RL-to-See-Them-All/Orsta-7B

Image-Text-to-Text • 8B • Updated Jun 4 • 1.45k • 10
One-RL-to-See-Them-All/Orsta-32B-0321

Image-Text-to-Text • 33B • Updated May 26 • 6
One-RL-to-See-Them-All/Orsta-32B-0326

Image-Text-to-Text • 33B • Updated Jun 4 • 11 • 5
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 596 • 95
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 35
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 89

Scaling Law for Quantization-Aware Training

Paper • 2505.14302 • Published May 20 • 76
Reward Reasoning Model

Paper • 2505.14674 • Published May 20 • 37
Qwen3 Technical Report

Paper • 2505.09388 • Published May 14 • 276
AdaptThink: Reasoning Models Can Learn When to Think

Paper • 2505.13417 • Published May 19 • 82

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Paper • 2505.09568 • Published May 14 • 97
Qwen3 Technical Report

Paper • 2505.09388 • Published May 14 • 276
GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning

Paper • 2505.11049 • Published May 16 • 61
Emerging Properties in Unified Multimodal Pretraining

Paper • 2505.14683 • Published May 20 • 133

Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities

Paper • 2505.02567 • Published May 5 • 79
TabSTAR: A Foundation Tabular Model With Semantically Target-Aware Representations

Paper • 2505.18125 • Published May 23 • 113
Distilling LLM Agent into Small Models with Retrieval and Code Tools

Paper • 2505.17612 • Published May 23 • 81
One RL to See Them All: Visual Triple Unified Reinforcement Learning

Paper • 2505.18129 • Published May 23 • 60

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