Collections
Discover the best community collections!
Collections including paper arxiv:2509.09674
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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 • 20 -
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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Unified Vision-Language-Action Model
Paper • 2506.19850 • Published • 28 -
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Paper • 2506.01844 • Published • 158 -
3D-VLA: A 3D Vision-Language-Action Generative World Model
Paper • 2403.09631 • Published • 12 -
QUAR-VLA: Vision-Language-Action Model for Quadruped Robots
Paper • 2312.14457 • Published • 1
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Gemini Robotics: Bringing AI into the Physical World
Paper • 2503.20020 • Published • 31 -
Magma: A Foundation Model for Multimodal AI Agents
Paper • 2502.13130 • Published • 58 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
Paper • 2410.23218 • Published • 49
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 60 -
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 • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
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SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
Paper • 2509.09674 • Published • 80 -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 193 -
QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs
Paper • 2510.11696 • Published • 182
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A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
Paper • 2507.01925 • Published • 39 -
DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge
Paper • 2507.04447 • Published • 45 -
A Survey on Vision-Language-Action Models for Autonomous Driving
Paper • 2506.24044 • Published • 14 -
EmbRACE-3K: Embodied Reasoning and Action in Complex Environments
Paper • 2507.10548 • Published • 37
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microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 15.7k • 1.43k -
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Paper • 2504.10449 • Published • 15 -
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct
Text Generation • 8B • Updated • 99 • 17 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63
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Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering
Paper • 2411.11504 • Published • 24 -
Top-nσ: Not All Logits Are You Need
Paper • 2411.07641 • Published • 24 -
Adaptive Decoding via Latent Preference Optimization
Paper • 2411.09661 • Published • 10 -
When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training
Paper • 2411.13476 • Published • 16
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 30 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
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
-
SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning
Paper • 2509.09674 • Published • 80 -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 193 -
QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs
Paper • 2510.11696 • Published • 182
-
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 • 20 -
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
-
A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
Paper • 2507.01925 • Published • 39 -
DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge
Paper • 2507.04447 • Published • 45 -
A Survey on Vision-Language-Action Models for Autonomous Driving
Paper • 2506.24044 • Published • 14 -
EmbRACE-3K: Embodied Reasoning and Action in Complex Environments
Paper • 2507.10548 • Published • 37
-
Unified Vision-Language-Action Model
Paper • 2506.19850 • Published • 28 -
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Paper • 2506.01844 • Published • 158 -
3D-VLA: A 3D Vision-Language-Action Generative World Model
Paper • 2403.09631 • Published • 12 -
QUAR-VLA: Vision-Language-Action Model for Quadruped Robots
Paper • 2312.14457 • Published • 1
-
microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 15.7k • 1.43k -
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Paper • 2504.10449 • Published • 15 -
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct
Text Generation • 8B • Updated • 99 • 17 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63
-
Gemini Robotics: Bringing AI into the Physical World
Paper • 2503.20020 • Published • 31 -
Magma: A Foundation Model for Multimodal AI Agents
Paper • 2502.13130 • Published • 58 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
Paper • 2410.23218 • Published • 49
-
Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering
Paper • 2411.11504 • Published • 24 -
Top-nσ: Not All Logits Are You Need
Paper • 2411.07641 • Published • 24 -
Adaptive Decoding via Latent Preference Optimization
Paper • 2411.09661 • Published • 10 -
When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training
Paper • 2411.13476 • Published • 16
-
LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 60 -
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 • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 30 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
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