Noam Shazeer
3 papers · Latest:
PaLM: Scaling Language Modeling with Pathways
PaLM is a 540-billion parameter Transformer language model that achieves state-of-the-art few-shot learning performance across diverse benchmarks, demonstrating significant benefits from scaling.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
This paper introduces a unified text-to-text framework for transfer learning in NLP, achieving state-of-the-art results across diverse language tasks by systematically exploring pre-training and fine-tuning strategies.
Attention Is All You Need
The paper introduces the Transformer, a novel neural network architecture based solely on attention mechanisms that outperforms traditional recurrent and convolutional models in sequence transduction tasks like machine translation.
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