Papers with ICL generalization

1 papers
Multi-Task Transfer Matters During Instruction-Tuning (2024.findings-acl)

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Challenge: Instruction-tuning improves a model’s ability to learn in-context, but the mechanisms that drive in-constext learning are poorly understood.
Approach: They propose to train a model on hundreds of tasks to improve its ability to learn in-context.
Outcome: The proposed methods improve model transfer and in-context generalization, suggesting catastrophic forgetting may impact in-constext learning.

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