Collection by 
Jul 14, 2025
Collections
Discover the best community collections!
Collections including paper arxiv:2507.07095
Collection by 
5 days ago
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DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training
Paper • 2504.17565 • Published • 2 -
AI-MO/NuminaMath-1.5
Viewer • Updated • 896k • 2.75k • 183 -
PrimeIntellect/synthetic-code-understanding
Viewer • Updated • 60.6k • 45 • 20 -
Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data
Paper • 2507.07095 • Published • 56
Collection by 
Dec 26, 2025
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MotionLLM: Understanding Human Behaviors from Human Motions and Videos
Paper • 2405.20340 • Published • 20 -
Spectrally Pruned Gaussian Fields with Neural Compensation
Paper • 2405.00676 • Published • 10 -
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
Paper • 2404.18212 • Published • 30 -
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Paper • 2405.00732 • Published • 122
Collection by 
Jan 12
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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
Collection by 
Jul 10, 2025
Collection by 
Jul 10, 2025
Collection by 
Feb 12
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MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 21 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 16 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31
Collection by 
8 days ago
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 153 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collection by Jul 14, 2025
Collection by Jul 10, 2025
Collection by 5 days ago
-
DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training
Paper • 2504.17565 • Published • 2 -
AI-MO/NuminaMath-1.5
Viewer • Updated • 896k • 2.75k • 183 -
PrimeIntellect/synthetic-code-understanding
Viewer • Updated • 60.6k • 45 • 20 -
Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data
Paper • 2507.07095 • Published • 56
Collection by Jul 10, 2025
Collection by Dec 26, 2025
-
MotionLLM: Understanding Human Behaviors from Human Motions and Videos
Paper • 2405.20340 • Published • 20 -
Spectrally Pruned Gaussian Fields with Neural Compensation
Paper • 2405.00676 • Published • 10 -
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
Paper • 2404.18212 • Published • 30 -
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Paper • 2405.00732 • Published • 122
Collection by Feb 12
-
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 21 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 17 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 16 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 31
Collection by Jan 12
-
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
Collection by 8 days ago
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 153 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25