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Diffusion Models are Evolutionary Algorithms
Paper • 2410.02543 • Published -
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Paper • 2003.03384 • Published -
One pixel attack for fooling deep neural networks
Paper • 1710.08864 • Published -
Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
Paper • 2601.20861 • Published • 1
Collections
Discover the best community collections!
Collections including paper arxiv:2505.22954
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Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 120 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 146
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BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 107 -
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Paper • 2310.11511 • Published • 80 -
In-Context Learning Creates Task Vectors
Paper • 2310.15916 • Published • 43 -
Matryoshka Diffusion Models
Paper • 2310.15111 • Published • 45
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Demystifying Reinforcement Learning in Agentic Reasoning
Paper • 2510.11701 • Published • 33 -
LoongRL:Reinforcement Learning for Advanced Reasoning over Long Contexts
Paper • 2510.19363 • Published • 63 -
Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Paper • 2510.25992 • Published • 48 -
Teaching Pretrained Language Models to Think Deeper with Retrofitted Recurrence
Paper • 2511.07384 • Published • 19
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GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
Paper • 2503.14734 • Published • 7 -
Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation
Paper • 2401.02117 • Published • 33 -
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Paper • 2506.01844 • Published • 158 -
Vision-Guided Chunking Is All You Need: Enhancing RAG with Multimodal Document Understanding
Paper • 2506.16035 • Published • 89
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The Lessons of Developing Process Reward Models in Mathematical Reasoning
Paper • 2501.07301 • Published • 100 -
Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2
Paper • 2502.03544 • Published • 44 -
FoNE: Precise Single-Token Number Embeddings via Fourier Features
Paper • 2502.09741 • Published • 15 -
SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers
Paper • 2502.20545 • Published • 22
-
Diffusion Models are Evolutionary Algorithms
Paper • 2410.02543 • Published -
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Paper • 2003.03384 • Published -
One pixel attack for fooling deep neural networks
Paper • 1710.08864 • Published -
Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
Paper • 2601.20861 • Published • 1
-
Demystifying Reinforcement Learning in Agentic Reasoning
Paper • 2510.11701 • Published • 33 -
LoongRL:Reinforcement Learning for Advanced Reasoning over Long Contexts
Paper • 2510.19363 • Published • 63 -
Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Paper • 2510.25992 • Published • 48 -
Teaching Pretrained Language Models to Think Deeper with Retrofitted Recurrence
Paper • 2511.07384 • Published • 19
-
GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
Paper • 2503.14734 • Published • 7 -
Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation
Paper • 2401.02117 • Published • 33 -
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Paper • 2506.01844 • Published • 158 -
Vision-Guided Chunking Is All You Need: Enhancing RAG with Multimodal Document Understanding
Paper • 2506.16035 • Published • 89
-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 120 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 146
-
The Lessons of Developing Process Reward Models in Mathematical Reasoning
Paper • 2501.07301 • Published • 100 -
Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2
Paper • 2502.03544 • Published • 44 -
FoNE: Precise Single-Token Number Embeddings via Fourier Features
Paper • 2502.09741 • Published • 15 -
SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers
Paper • 2502.20545 • Published • 22
-
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 107 -
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Paper • 2310.11511 • Published • 80 -
In-Context Learning Creates Task Vectors
Paper • 2310.15916 • Published • 43 -
Matryoshka Diffusion Models
Paper • 2310.15111 • Published • 45