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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 • 14 -
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:2508.15260
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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 • 84 -
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
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 216 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
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Parallel-R1: Towards Parallel Thinking via Reinforcement Learning
Paper • 2509.07980 • Published • 99 -
ParaThinker: Native Parallel Thinking as a New Paradigm to Scale LLM Test-time Compute
Paper • 2509.04475 • Published • 3 -
Don't Overthink it. Preferring Shorter Thinking Chains for Improved LLM Reasoning
Paper • 2505.17813 • Published • 57 -
Deep Think with Confidence
Paper • 2508.15260 • Published • 87
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Adapting Vision-Language Models Without Labels: A Comprehensive Survey
Paper • 2508.05547 • Published • 11 -
Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
Paper • 2508.10751 • Published • 28 -
SSRL: Self-Search Reinforcement Learning
Paper • 2508.10874 • Published • 94 -
Mind the Generation Process: Fine-Grained Confidence Estimation During LLM Generation
Paper • 2508.12040 • Published • 14
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Klear-Reasoner: Advancing Reasoning Capability via Gradient-Preserving Clipping Policy Optimization
Paper • 2508.07629 • Published • 41 -
Less Is More: Training-Free Sparse Attention with Global Locality for Efficient Reasoning
Paper • 2508.07101 • Published • 13 -
Compressing Chain-of-Thought in LLMs via Step Entropy
Paper • 2508.03346 • Published • 7 -
Train Long, Think Short: Curriculum Learning for Efficient Reasoning
Paper • 2508.08940 • Published • 26
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Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations
Paper • 2508.09789 • Published • 5 -
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Paper • 2508.13186 • Published • 18 -
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents
Paper • 2508.04038 • Published • 1 -
Prompt Orchestration Markup Language
Paper • 2508.13948 • Published • 48
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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 • 14 -
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
-
Klear-Reasoner: Advancing Reasoning Capability via Gradient-Preserving Clipping Policy Optimization
Paper • 2508.07629 • Published • 41 -
Less Is More: Training-Free Sparse Attention with Global Locality for Efficient Reasoning
Paper • 2508.07101 • Published • 13 -
Compressing Chain-of-Thought in LLMs via Step Entropy
Paper • 2508.03346 • Published • 7 -
Train Long, Think Short: Curriculum Learning for Efficient Reasoning
Paper • 2508.08940 • Published • 26
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
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
-
Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations
Paper • 2508.09789 • Published • 5 -
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Paper • 2508.13186 • Published • 18 -
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents
Paper • 2508.04038 • Published • 1 -
Prompt Orchestration Markup Language
Paper • 2508.13948 • Published • 48
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 216 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
Parallel-R1: Towards Parallel Thinking via Reinforcement Learning
Paper • 2509.07980 • Published • 99 -
ParaThinker: Native Parallel Thinking as a New Paradigm to Scale LLM Test-time Compute
Paper • 2509.04475 • Published • 3 -
Don't Overthink it. Preferring Shorter Thinking Chains for Improved LLM Reasoning
Paper • 2505.17813 • Published • 57 -
Deep Think with Confidence
Paper • 2508.15260 • Published • 87
-
Adapting Vision-Language Models Without Labels: A Comprehensive Survey
Paper • 2508.05547 • Published • 11 -
Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
Paper • 2508.10751 • Published • 28 -
SSRL: Self-Search Reinforcement Learning
Paper • 2508.10874 • Published • 94 -
Mind the Generation Process: Fine-Grained Confidence Estimation During LLM Generation
Paper • 2508.12040 • Published • 14