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An interpretable and efficient predictor using pre-trained models
...The final model (which we call Emb-GAM) is a transparent, linear function of its input features and feature interactions. Leveraging the language model allows Emb-GAM to learn far fewer linear coefficients, model larger interactions, and generalize well to novel inputs. Across a variety of natural-language-processing datasets, Emb-GAM achieves strong prediction performance without sacrificing interpretability.
SYRAH si propone di far emergere e rappresentare i concetti espressi per mezzo di un linguaggio naturale. SYRAH aims to discover and represent concepts expressed in natural languages. NLP, lemma, lemmario, italiano, rete, semantica, clustering, semantic