Papers with Instruction Fine-tuning

1 papers
Learning or Self-aligning? Rethinking Instruction Fine-tuning (2024.acl-long)

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Challenge: Instruction fine-tuning (IFT) is a crucial phase in building large language models (LLMs).
Approach: They propose a knowledge intervention framework to decouple the potential underlying factors of IFT and enable individual analysis of different factors.
Outcome: The proposed framework decouples the potential underlying factors of IFT, enabling individual analysis of different factors.

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