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Memory Augmented Language Models through Mixture of Word Experts
Paper • 2311.10768 • Published • 18 -
System 2 Attention (is something you might need too)
Paper • 2311.11829 • Published • 44 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 30 -
Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 77
Collections
Discover the best community collections!
Collections including paper arxiv:2311.11045
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PDFTriage: Question Answering over Long, Structured Documents
Paper • 2309.08872 • Published • 53 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 81 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 41 -
Context-Aware Meta-Learning
Paper • 2310.10971 • Published • 17
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Visual In-Context Prompting
Paper • 2311.13601 • Published • 19 -
Textbooks Are All You Need
Paper • 2306.11644 • Published • 146 -
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Paper • 2308.08155 • Published • 10 -
LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models
Paper • 2303.02927 • Published • 3
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Textbooks Are All You Need
Paper • 2306.11644 • Published • 146 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 36 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104
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Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 50 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 31 -
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Paper • 2304.12244 • Published • 13 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
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OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
Paper • 2404.14619 • Published • 126 -
Scaling Laws for Downstream Task Performance of Large Language Models
Paper • 2402.04177 • Published • 19 -
Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 77 -
Orca-Math: Unlocking the potential of SLMs in Grade School Math
Paper • 2402.14830 • Published • 25
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Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Paper • 2402.14848 • Published • 20 -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 50 -
How Far Are We from Intelligent Visual Deductive Reasoning?
Paper • 2403.04732 • Published • 23 -
Learning to Reason and Memorize with Self-Notes
Paper • 2305.00833 • Published • 5
-
Memory Augmented Language Models through Mixture of Word Experts
Paper • 2311.10768 • Published • 18 -
System 2 Attention (is something you might need too)
Paper • 2311.11829 • Published • 44 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 30 -
Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 77
-
Textbooks Are All You Need
Paper • 2306.11644 • Published • 146 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 36 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104
-
PDFTriage: Question Answering over Long, Structured Documents
Paper • 2309.08872 • Published • 53 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 81 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 41 -
Context-Aware Meta-Learning
Paper • 2310.10971 • Published • 17
-
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 50 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 31 -
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Paper • 2304.12244 • Published • 13 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
-
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
Paper • 2404.14619 • Published • 126 -
Scaling Laws for Downstream Task Performance of Large Language Models
Paper • 2402.04177 • Published • 19 -
Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 77 -
Orca-Math: Unlocking the potential of SLMs in Grade School Math
Paper • 2402.14830 • Published • 25
-
Visual In-Context Prompting
Paper • 2311.13601 • Published • 19 -
Textbooks Are All You Need
Paper • 2306.11644 • Published • 146 -
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Paper • 2308.08155 • Published • 10 -
LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models
Paper • 2303.02927 • Published • 3
-
Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Paper • 2402.14848 • Published • 20 -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 50 -
How Far Are We from Intelligent Visual Deductive Reasoning?
Paper • 2403.04732 • Published • 23 -
Learning to Reason and Memorize with Self-Notes
Paper • 2305.00833 • Published • 5