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Sep 15
Sep 15Collections
Discover the best community collections!
Collections including paper arxiv:2506.06941
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Jun 29
Jun 29Collection by
Nov 3
Nov 3-
Nuclear Norm Regularization for Deep Learning
Paper • 2405.14544 • Published • 1 -
Token embeddings violate the manifold hypothesis
Paper • 2504.01002 • Published • 1 -
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
Paper • 2403.10476 • Published • 1 -
ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning
Paper • 2504.00254 • Published • 1
Collection by
Aug 21
Aug 21-
Yume: An Interactive World Generation Model
Paper • 2507.17744 • Published • 87 -
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
Collection by
Aug 31
Aug 31-
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
Paper • 2506.06395 • Published • 133 -
Magistral
Paper • 2506.10910 • Published • 65 -
Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs
Paper • 2506.07240 • Published • 7 -
Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation
Paper • 2506.09991 • Published • 55
Collection by
15 days ago
15 days ago-
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs
Paper • 2501.18585 • Published • 61 -
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!
Paper • 2502.07374 • Published • 40 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 153 -
S*: Test Time Scaling for Code Generation
Paper • 2502.14382 • Published • 63
Collection by
Sep 15
Sep 15Collection by
Aug 21
Aug 21-
Yume: An Interactive World Generation Model
Paper • 2507.17744 • Published • 87 -
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
Collection by
Jun 29
Jun 29Collection by
Aug 31
Aug 31-
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
Paper • 2506.06395 • Published • 133 -
Magistral
Paper • 2506.10910 • Published • 65 -
Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs
Paper • 2506.07240 • Published • 7 -
Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation
Paper • 2506.09991 • Published • 55
Collection by
Nov 3
Nov 3-
Nuclear Norm Regularization for Deep Learning
Paper • 2405.14544 • Published • 1 -
Token embeddings violate the manifold hypothesis
Paper • 2504.01002 • Published • 1 -
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
Paper • 2403.10476 • Published • 1 -
ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning
Paper • 2504.00254 • Published • 1
Collection by
15 days ago
15 days ago-
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs
Paper • 2501.18585 • Published • 61 -
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!
Paper • 2502.07374 • Published • 40 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 153 -
S*: Test Time Scaling for Code Generation
Paper • 2502.14382 • Published • 63