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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 • 17 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4
Collections
Discover the best community collections!
Collections including paper arxiv:2306.11644
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Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 46 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 25 -
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 • 45
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Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 101 -
Textbooks Are All You Need
Paper • 2306.11644 • Published • 139 -
Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 99 -
Large Language Models Struggle to Learn Long-Tail Knowledge
Paper • 2211.08411 • Published • 3
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A Survey on Language Models for Code
Paper • 2311.07989 • Published • 21 -
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Paper • 2310.06770 • Published • 3 -
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Paper • 2401.03065 • Published • 10 -
Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming
Paper • 2402.14261 • Published • 10
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Nemotron-4 15B Technical Report
Paper • 2402.16819 • Published • 40 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 50 -
RWKV: Reinventing RNNs for the Transformer Era
Paper • 2305.13048 • Published • 10 -
Reformer: The Efficient Transformer
Paper • 2001.04451 • Published
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Visual In-Context Prompting
Paper • 2311.13601 • Published • 14 -
Textbooks Are All You Need
Paper • 2306.11644 • Published • 139 -
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Paper • 2308.08155 • Published • 2 -
LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models
Paper • 2303.02927 • Published • 3