Papers by Antoine Liutkus

1 papers
Black-box language model explanation by context length probing (2023.acl-short)

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Challenge: *context length probing* is a new explanation technique for large language models . it tracks the predictions of a model as a function of the length of available context .
Approach: They propose a method that tracks the predictions of a model as a function of the length of available context and allows to assign *differential importance scores* to different contexts.
Outcome: The proposed method is model-agnostic and does not rely on access to model internals beyond token-level probabilities.

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