Collections
Discover the best community collections!
Collections including paper arxiv:2508.06471
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Attention Is All You Need
Paper • 1706.03762 • Published • 147 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 12 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 13 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
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Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment
Paper • 2505.10597 • Published -
COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values
Paper • 2504.05535 • Published • 43 -
nvidia/HelpSteer3
Viewer • Updated • 133k • 19.2k • 120 -
nvidia/Nemotron-RL-instruction_following
RL Environment • Updated • 1.46k • 25
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Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 20 -
Evaluating Large Language Models Trained on Code
Paper • 2107.03374 • Published • 12 -
Training language models to follow instructions with human feedback
Paper • 2203.02155 • Published • 26 -
GPT-4 Technical Report
Paper • 2303.08774 • Published • 5
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Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 519 -
zai-org/GLM-4.6
Text Generation • 357B • Updated • 25.3k • • 1.25k -
deepseek-ai/DeepSeek-R1
Text Generation • 684B • Updated • 1.69M • • 14.4k -
deepseek-ai/DeepSeek-V3.2-Exp
Text Generation • 685B • Updated • 42.8k • • 1.03k
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Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 279 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 263 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 255 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 261
-
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 20 -
Evaluating Large Language Models Trained on Code
Paper • 2107.03374 • Published • 12 -
Training language models to follow instructions with human feedback
Paper • 2203.02155 • Published • 26 -
GPT-4 Technical Report
Paper • 2303.08774 • Published • 5
-
Attention Is All You Need
Paper • 1706.03762 • Published • 147 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 12 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 13 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
-
Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment
Paper • 2505.10597 • Published -
COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values
Paper • 2504.05535 • Published • 43 -
nvidia/HelpSteer3
Viewer • Updated • 133k • 19.2k • 120 -
nvidia/Nemotron-RL-instruction_following
RL Environment • Updated • 1.46k • 25
-
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 519 -
zai-org/GLM-4.6
Text Generation • 357B • Updated • 25.3k • • 1.25k -
deepseek-ai/DeepSeek-R1
Text Generation • 684B • Updated • 1.69M • • 14.4k -
deepseek-ai/DeepSeek-V3.2-Exp
Text Generation • 685B • Updated • 42.8k • • 1.03k
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 279 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 263 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 255 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 261