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microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 5.69k • 1.24k -
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 • 358 • 15 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63
Collections
Discover the best community collections!
Collections including paper arxiv:2508.11737
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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 • 85 -
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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Yume: An Interactive World Generation Model
Paper • 2507.17744 • Published • 89 -
SSRL: Self-Search Reinforcement Learning
Paper • 2508.10874 • Published • 97 -
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
Paper • 2506.06941 • Published • 15 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 187
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Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models
Paper • 2505.04921 • Published • 185 -
On Path to Multimodal Generalist: General-Level and General-Bench
Paper • 2505.04620 • Published • 82 -
StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant
Paper • 2505.05467 • Published • 13 -
Adapting Vision-Language Models Without Labels: A Comprehensive Survey
Paper • 2508.05547 • Published • 11
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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 • 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
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internlm/Intern-S1
Image-Text-to-Text • 241B • Updated • 47.9k • 250 -
Intern-S1: A Scientific Multimodal Foundation Model
Paper • 2508.15763 • Published • 259 -
MiniCPM-V: A GPT-4V Level MLLM on Your Phone
Paper • 2408.01800 • Published • 88 -
openbmb/MiniCPM-V-4_5
Image-Text-to-Text • 9B • Updated • 41.9k • 1.04k
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Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 89 -
LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale
Paper • 2504.16030 • Published • 36 -
Time Blindness: Why Video-Language Models Can't See What Humans Can?
Paper • 2505.24867 • Published • 80 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 250
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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34
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microsoft/bitnet-b1.58-2B-4T
Text Generation • 0.8B • Updated • 5.69k • 1.24k -
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 • 358 • 15 -
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63
-
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 • 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
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
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
-
internlm/Intern-S1
Image-Text-to-Text • 241B • Updated • 47.9k • 250 -
Intern-S1: A Scientific Multimodal Foundation Model
Paper • 2508.15763 • Published • 259 -
MiniCPM-V: A GPT-4V Level MLLM on Your Phone
Paper • 2408.01800 • Published • 88 -
openbmb/MiniCPM-V-4_5
Image-Text-to-Text • 9B • Updated • 41.9k • 1.04k
-
Yume: An Interactive World Generation Model
Paper • 2507.17744 • Published • 89 -
SSRL: Self-Search Reinforcement Learning
Paper • 2508.10874 • Published • 97 -
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
Paper • 2506.06941 • Published • 15 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 187
-
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 89 -
LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale
Paper • 2504.16030 • Published • 36 -
Time Blindness: Why Video-Language Models Can't See What Humans Can?
Paper • 2505.24867 • Published • 80 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 250
-
Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models
Paper • 2505.04921 • Published • 185 -
On Path to Multimodal Generalist: General-Level and General-Bench
Paper • 2505.04620 • Published • 82 -
StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant
Paper • 2505.05467 • Published • 13 -
Adapting Vision-Language Models Without Labels: A Comprehensive Survey
Paper • 2508.05547 • Published • 11
-
iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34