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cs.LG2025
ALICE: An Interpretable Neural Architecture for Generalization in Substitution Ciphers
Jeff Shen, Lindsay M. Smith
We present cryptogram solving as an ideal testbed for studying neural network reasoning and generalization; models must decrypt text encoded with substitution ciphers, choosing fro…
cs.LG2025
When can in-context learning generalize out of task distribution?
Chase Goddard, Lindsay M. Smith, Vudtiwat Ngampruetikorn +1
In-context learning (ICL) is a remarkable capability of pretrained transformers that allows models to generalize to unseen tasks after seeing only a few examples. We investigate em…