In-context learning learns label relationships but is not conventional learning
The predictions of Large Language Models (LLMs) on downstream tasks often improve significantly when including examples of the input–label relationship in the context. However, there is currently no consensus about how this in-context learning (ICL) ability of LLMs works. For example, while Xie et a...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
OpenReview
2024
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