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OpenAI GPT-3: Language Models are Few-Shot Learners

Machine Learning Street Talk (MLST)

CHAPTER

Memorization vs Reasoning in Language Models

This chapter explores the distinctions between memorization and reasoning in language models, emphasizing their reliance on learned patterns from training data. The discussion includes the complexities of word unscrambling versus scrambling, questioning the true understanding behind the model's abilities and highlighting the limitations of their training experience.

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