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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 • 34 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 97
Collections
Discover the best community collections!
Collections including paper arxiv:2307.08701
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Self-Instruct: Aligning Language Model with Self Generated Instructions
Paper • 2212.10560 • Published • 9 -
Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4
Paper • 2312.16171 • Published • 35 -
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
Paper • 2401.14196 • Published • 60 -
AlpaCare:Instruction-tuned Large Language Models for Medical Application
Paper • 2310.14558 • Published • 4
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The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
Paper • 2210.14986 • Published • 5 -
Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2
Paper • 2311.10702 • Published • 20 -
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 76 -
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
Paper • 2309.04269 • Published • 33
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AlpaGasus: Training A Better Alpaca with Fewer Data
Paper • 2307.08701 • Published • 23 -
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Paper • 2303.03915 • Published • 7 -
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
Paper • 2309.04662 • Published • 23 -
SlimPajama-DC: Understanding Data Combinations for LLM Training
Paper • 2309.10818 • Published • 11
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 5 -
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 • 12 -
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 • 5 -
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 • 19 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4
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MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning
Paper • 2310.09478 • Published • 21 -
Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams
Paper • 2310.08678 • Published • 14 -
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 244 -
LLaMA: Open and Efficient Foundation Language Models
Paper • 2302.13971 • Published • 14