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cs.CL2022★ 59 cited
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
Shivam Garg, Dimitris Tsipras, Percy Liang +1
In-context learning refers to the ability of a model to condition on a prompt sequence consisting of in-context examples (input-output pairs corresponding to some task) along with…
math.ST2022★ 3 cited
On the Statistical Complexity of Sample Amplification
Brian Axelrod, Shivam Garg, Yanjun Han +2
The ``sample amplification'' problem formalizes the following question: Given i.i.d. samples drawn from an unknown distribution , when is it possible to produce a larger set…