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Attention Is All You Need
Paper • 1706.03762 • Published • 120 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 10 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
Collections
Discover the best community collections!
Collections including paper arxiv:2501.04519
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Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 305 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 308 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 55 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
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A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale
Paper • 2309.06497 • Published • 7 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 251
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Rewnozom/agent-zero-v1-a-01
Text Generation • 4B • Updated • 15 • 2 -
TheBloke/MythoMax-L2-13B-GGUF
13B • Updated • 60.1k • 229 -
DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-GGUF
Text Generation • 18B • Updated • 56.5k • 528 -
QuantFactory/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored-GGUF
Text Generation • 8B • Updated • 9.08k • 141
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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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Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 86 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 22 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 57 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
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S*: Test Time Scaling for Code Generation
Paper • 2502.14382 • Published • 63 -
S^2R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning
Paper • 2502.12853 • Published • 29 -
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 290 -
Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search
Paper • 2502.02508 • Published • 22
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Attention Is All You Need
Paper • 1706.03762 • Published • 120 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 10 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
-
A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale
Paper • 2309.06497 • Published • 7 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 251
-
Rewnozom/agent-zero-v1-a-01
Text Generation • 4B • Updated • 15 • 2 -
TheBloke/MythoMax-L2-13B-GGUF
13B • Updated • 60.1k • 229 -
DavidAU/Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4B-GGUF
Text Generation • 18B • Updated • 56.5k • 528 -
QuantFactory/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored-GGUF
Text Generation • 8B • Updated • 9.08k • 141
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Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 305 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 308 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 55 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
-
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
-
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 86 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 22 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 57 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
-
S*: Test Time Scaling for Code Generation
Paper • 2502.14382 • Published • 63 -
S^2R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning
Paper • 2502.12853 • Published • 29 -
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 290 -
Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search
Paper • 2502.02508 • Published • 22