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Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 37 -
Efficient Estimation of Word Representations in Vector Space
Paper • 1301.3781 • Published • 6 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
Attention Is All You Need
Paper • 1706.03762 • Published • 50
Collections
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Collections including paper arxiv:1706.03762
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sentence-transformers/all-mpnet-base-v2
Sentence Similarity • Updated • 19.4M • • 948 -
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Paper • 1910.10683 • Published • 10 -
google-t5/t5-base
Translation • Updated • 2.19M • • 656 -
Attention Is All You Need
Paper • 1706.03762 • Published • 50
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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
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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 • 3 -
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 • 50 -
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 • 12
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Self-Play Preference Optimization for Language Model Alignment
Paper • 2405.00675 • Published • 25 -
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Paper • 2205.14135 • Published • 11 -
Attention Is All You Need
Paper • 1706.03762 • Published • 50 -
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Paper • 2307.08691 • Published • 8