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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:2501.08313
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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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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 320 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 213
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MiniMaxAI/MiniMax-Text-01
Text Generation • Updated • 12.5k • 652 -
MiniMaxAI/MiniMax-VL-01
Image-Text-to-Text • Updated • 84.8k • 282 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
MiniMaxText01
💬121Chat with an AI model using text and images
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 153 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models
Paper • 2509.19371 • Published -
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Paper • 2505.06708 • Published • 11 -
Selective Attention: Enhancing Transformer through Principled Context Control
Paper • 2411.12892 • Published -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 193
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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
-
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
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 153 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
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
-
How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models
Paper • 2509.19371 • Published -
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Paper • 2505.06708 • Published • 11 -
Selective Attention: Enhancing Transformer through Principled Context Control
Paper • 2411.12892 • Published -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 193
-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 320 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 213
-
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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MiniMaxAI/MiniMax-Text-01
Text Generation • Updated • 12.5k • 652 -
MiniMaxAI/MiniMax-VL-01
Image-Text-to-Text • Updated • 84.8k • 282 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
MiniMaxText01
💬121Chat with an AI model using text and images
-
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