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Textbooks Are All You Need
Paper • 2306.11644 • Published • 142 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 87 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 33 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 94
Collections
Discover the best community collections!
Collections including paper arxiv:2308.06259
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Better Synthetic Data by Retrieving and Transforming Existing Datasets
Paper • 2404.14361 • Published • 1 -
Generative AI for Synthetic Data Generation: Methods, Challenges and the Future
Paper • 2403.04190 • Published -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 29 -
A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Models
Paper • 2404.14445 • Published
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Large Language Model Alignment: A Survey
Paper • 2309.15025 • Published • 2 -
Aligning Large Language Models with Human: A Survey
Paper • 2307.12966 • Published • 1 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 48 -
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Paper • 2310.05344 • Published • 1
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Self-Instruct: Aligning Language Model with Self Generated Instructions
Paper • 2212.10560 • Published • 8 -
Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4
Paper • 2312.16171 • Published • 34 -
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
Paper • 2401.14196 • Published • 47 -
AlpaCare:Instruction-tuned Large Language Models for Medical Application
Paper • 2310.14558 • Published • 4
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From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning
Paper • 2308.12032 • Published • 1 -
Know thy corpus! Robust methods for digital curation of Web corpora
Paper • 2003.06389 • Published • 1 -
Self-Alignment with Instruction Backtranslation
Paper • 2308.06259 • Published • 41 -
The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
Paper • 2305.06156 • Published • 2
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AlpaGasus: Training A Better Alpaca with Fewer Data
Paper • 2307.08701 • Published • 22 -
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Paper • 2303.03915 • Published • 6 -
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
Paper • 2309.04662 • Published • 22 -
SlimPajama-DC: Understanding Data Combinations for LLM Training
Paper • 2309.10818 • Published • 10
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4 -
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Paper • 2310.13127 • Published • 11 -
Evaluating the Robustness to Instructions of Large Language Models
Paper • 2308.14306 • Published • 1
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Paper • 2202.07922 • Published • 1 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 18 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4
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Moral Foundations of Large Language Models
Paper • 2310.15337 • Published • 1 -
Specific versus General Principles for Constitutional AI
Paper • 2310.13798 • Published • 2 -
Contrastive Prefence Learning: Learning from Human Feedback without RL
Paper • 2310.13639 • Published • 24 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 47