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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
Collections
Discover the best community collections!
Collections including paper arxiv:2406.11794
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Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 1 -
Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering
Paper • 2308.13259 • Published • 2 -
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Paper • 2309.05653 • Published • 10 -
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Paper • 2309.12284 • Published • 19
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DataComp-LM: In search of the next generation of training sets for language models
Paper • 2406.11794 • Published • 50 -
Training Language Models on Synthetic Edit Sequences Improves Code Synthesis
Paper • 2410.02749 • Published • 12 -
Fewer Truncations Improve Language Modeling
Paper • 2404.10830 • Published • 3 -
How to Train Long-Context Language Models (Effectively)
Paper • 2410.02660 • Published • 2
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Qwen2.5-Coder Technical Report
Paper • 2409.12186 • Published • 139 -
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
Paper • 2409.12122 • Published • 3 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 14 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 76
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DataComp-LM: In search of the next generation of training sets for language models
Paper • 2406.11794 • Published • 50 -
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
Paper • 2406.10209 • Published • 8 -
Transformers Can Do Arithmetic with the Right Embeddings
Paper • 2405.17399 • Published • 52 -
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Paper • 2406.11931 • Published • 58
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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 • 18 -
The Prompt Report: A Systematic Survey of Prompting Techniques
Paper • 2406.06608 • Published • 56 -
CRAG -- Comprehensive RAG Benchmark
Paper • 2406.04744 • Published • 44 -
Transformers meet Neural Algorithmic Reasoners
Paper • 2406.09308 • Published • 43
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MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 18 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 13 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 14 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 30
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DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 14 -
The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale
Paper • 2406.17557 • Published • 88 -
DataComp-LM: In search of the next generation of training sets for language models
Paper • 2406.11794 • Published • 50 -
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
Paper • 2402.14905 • Published • 126