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Collections including paper arXiv:2507.20984

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 199 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
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 • 88

Grove MoE: Towards Efficient and Superior MoE LLMs with Adjugate Experts

Paper • 2508.07785 • Published Aug 11 • 28
MoBE: Mixture-of-Basis-Experts for Compressing MoE-based LLMs

Paper • 2508.05257 • Published Aug 7 • 13
SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56
MiniCPM4: Ultra-Efficient LLMs on End Devices

Paper • 2506.07900 • Published Jun 9 • 92

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

Local deployment models

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Paper • 2508.06471 • Published Aug 8 • 189
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

Paper • 2507.01006 • Published Jul 1 • 237
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Paper • 2507.06261 • Published Jul 7 • 63
SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56
tencent/Hunyuan-0.5B-Instruct

Text Generation • 0.5B • Updated Aug 6 • 478 • 52
IndexTeam/Index-1.9B-Chat-GGUF

2B • Updated Jun 26, 2024 • 117 • 26
YannQi/R-4B

Image-Text-to-Text • 5B • Updated Sep 4 • 48.2k • 171

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56
Open Data Synthesis For Deep Research

Paper • 2509.00375 • Published Aug 30 • 68
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth

Paper • 2509.03867 • Published Sep 4 • 209

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 199 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
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 • 88

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Paper • 2508.06471 • Published Aug 8 • 189
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

Paper • 2507.01006 • Published Jul 1 • 237
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Paper • 2507.06261 • Published Jul 7 • 63
SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

Grove MoE: Towards Efficient and Superior MoE LLMs with Adjugate Experts

Paper • 2508.07785 • Published Aug 11 • 28
MoBE: Mixture-of-Basis-Experts for Compressing MoE-based LLMs

Paper • 2508.05257 • Published Aug 7 • 13
SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56
MiniCPM4: Ultra-Efficient LLMs on End Devices

Paper • 2506.07900 • Published Jun 9 • 92

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56
tencent/Hunyuan-0.5B-Instruct

Text Generation • 0.5B • Updated Aug 6 • 478 • 52
IndexTeam/Index-1.9B-Chat-GGUF

2B • Updated Jun 26, 2024 • 117 • 26
YannQi/R-4B

Image-Text-to-Text • 5B • Updated Sep 4 • 48.2k • 171

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56
Open Data Synthesis For Deep Research

Paper • 2509.00375 • Published Aug 30 • 68
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth

Paper • 2509.03867 • Published Sep 4 • 209

Local deployment models

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Paper • 2507.20984 • Published Jul 28 • 56

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