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Recurrent Neural Network Regularization
Paper • 1409.2329 • Published -
Pointer Networks
Paper • 1506.03134 • Published -
Order Matters: Sequence to sequence for sets
Paper • 1511.06391 • Published -
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
Paper • 1811.06965 • Published
Collections
Discover the best community collections!
Collections including paper arxiv:1706.03762
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Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face
Paper • 2401.13822 • Published -
Attention Is All You Need
Paper • 1706.03762 • Published • 52 -
HuggingFace's Transformers: State-of-the-art Natural Language Processing
Paper • 1910.03771 • Published • 16 -
Model Cards for Model Reporting
Paper • 1810.03993 • Published • 3
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sentence-transformers/all-mpnet-base-v2
Sentence Similarity • Updated • 32.6M • • 993 -
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Paper • 1910.10683 • Published • 11 -
google-t5/t5-base
Translation • Updated • 2.74M • • 667 -
Attention Is All You Need
Paper • 1706.03762 • Published • 52
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Addition is All You Need for Energy-efficient Language Models
Paper • 2410.00907 • Published • 145 -
Emu3: Next-Token Prediction is All You Need
Paper • 2409.18869 • Published • 94 -
An accurate detection is not all you need to combat label noise in web-noisy datasets
Paper • 2407.05528 • Published • 4 -
Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP
Paper • 2407.00402 • Published • 22
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Attention Is All You Need
Paper • 1706.03762 • Published • 52 -
Playing Atari with Deep Reinforcement Learning
Paper • 1312.5602 • Published -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 13