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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 • 13 -
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
Collections
Discover the best community collections!
Collections including paper arxiv:2504.03151
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MLLM-as-a-Judge for Image Safety without Human Labeling
Paper • 2501.00192 • Published • 30 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
Xmodel-2 Technical Report
Paper • 2412.19638 • Published • 27 -
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs
Paper • 2412.18925 • Published • 101
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VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks
Paper • 2504.05118 • Published • 24 -
T1: Tool-integrated Self-verification for Test-time Compute Scaling in Small Language Models
Paper • 2504.04718 • Published • 38 -
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement
Paper • 2504.03561 • Published • 17 -
Concept Lancet: Image Editing with Compositional Representation Transplant
Paper • 2504.02828 • Published • 16
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InfiR : Crafting Effective Small Language Models and Multimodal Small Language Models in Reasoning
Paper • 2502.11573 • Published • 8 -
Boosting Multimodal Reasoning with MCTS-Automated Structured Thinking
Paper • 2502.02339 • Published • 22 -
video-SALMONN-o1: Reasoning-enhanced Audio-visual Large Language Model
Paper • 2502.11775 • Published • 8 -
Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Paper • 2412.18319 • Published • 40
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RL + Transformer = A General-Purpose Problem Solver
Paper • 2501.14176 • Published • 28 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 29 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 120 -
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Paper • 2412.12098 • Published • 5