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Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data
Autor:
Castro-Gonzalez, Leonardo, Chung, Yi-Ling, Kirk, Hannak Rose, Francis, John, Williams, Angus R., Johansson, Pica, Bright, Jonathan
The field of machine learning has recently made significant progress in reducing the requirements for labelled training data when building new models. These `cheaper' learning techniques hold significant potential for the social sciences, where devel
Externí odkaz:
http://arxiv.org/abs/2401.12295