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Traditional NLP Alignment
In its traditional sense within Natural Language Processing, 'alignment' refers to the task of linking corresponding components across two distinct sets of data. A classic application of this is word alignment in machine translation, where words in a source sentence are matched with their translated equivalents in a target sentence.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Computing Sciences
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Traditional NLP Alignment
LLM Alignment with Human Expectations
AI Alignment
A research team is developing a machine translation system and focuses on 'word alignment,' which involves mapping each word in a source sentence to its corresponding word in the translated sentence. Separately, a company developing a conversational AI is focused on 'model alignment,' which involves training the AI to be helpful, harmless, and honest. What is the core distinction between the concept of 'alignment' in these two contexts?
The Evolving Meaning of 'Alignment' in Language Models
Distinguishing Types of NLP Alignment