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SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 250 -
Demystifying Long Chain-of-Thought Reasoning in LLMs
Paper • 2502.03373 • Published • 58 -
Kimi k1.5: Scaling Reinforcement Learning with LLMs
Paper • 2501.12599 • Published • 125 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 123
Collections
Discover the best community collections!
Collections including paper arxiv:2502.02737
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Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning
Paper • 2311.11077 • Published • 29 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 90 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 54 -
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 66
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CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generation
Paper • 2502.08639 • Published • 43 -
TransMLA: Multi-head Latent Attention Is All You Need
Paper • 2502.07864 • Published • 58 -
Next Block Prediction: Video Generation via Semi-Autoregressive Modeling
Paper • 2502.07737 • Published • 9 -
Enhance-A-Video: Better Generated Video for Free
Paper • 2502.07508 • Published • 21
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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 53 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 33 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 22
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REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 103 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
Towards Best Practices for Open Datasets for LLM Training
Paper • 2501.08365 • Published • 63 -
Qwen2.5-1M Technical Report
Paper • 2501.15383 • Published • 72
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SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 250 -
Demystifying Long Chain-of-Thought Reasoning in LLMs
Paper • 2502.03373 • Published • 58 -
Kimi k1.5: Scaling Reinforcement Learning with LLMs
Paper • 2501.12599 • Published • 125 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 123
-
Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning
Paper • 2311.11077 • Published • 29 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 90 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 54 -
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 66
-
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 53 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 33 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 22
-
CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generation
Paper • 2502.08639 • Published • 43 -
TransMLA: Multi-head Latent Attention Is All You Need
Paper • 2502.07864 • Published • 58 -
Next Block Prediction: Video Generation via Semi-Autoregressive Modeling
Paper • 2502.07737 • Published • 9 -
Enhance-A-Video: Better Generated Video for Free
Paper • 2502.07508 • Published • 21
-
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 103 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
Towards Best Practices for Open Datasets for LLM Training
Paper • 2501.08365 • Published • 63 -
Qwen2.5-1M Technical Report
Paper • 2501.15383 • Published • 72