ASSET Seminar: “How do LLMs generalize on out-of-distribution tasks? insights from model’s internal representations”
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Amy Gutmann Hall, Room 414
3333 Chestnut Street, Philadelphia, United States
A mystery of large language models (LLMs) is their ability to solve novel tasks, notably through a few demonstrations in the prompt (in-context learning). Such tasks often require the model to generalize far beyond its training distribution, raising the question: how do LLMs achieve this form of out-of-distribution (OOD) generalization? For example, in symbolized language […]

