Papers by Tomer Natan

1 papers
In-context Learning and Gradient Descent Revisited (2024.naacl-long)

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Challenge: In-context learning (ICL) has shown impressive results in few-shot learning tasks, yet its underlying mechanism remains elusive.
Approach: They propose a simple gradient descent-based optimization procedure that respects layer causality and improves similarity scores significantly.
Outcome: The proposed procedure improves similarity scores on untrained models despite not showing ICL.

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