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pro vyhledávání: '"Sevegnani, Karin"'
Autor:
Sevegnani, Karin, Seshadri, Arjun, Wang, Tian, Beniwal, Anurag, McAuley, Julian, Lu, Alan, Medioni, Gerard
Recommender systems and search are both indispensable in facilitating personalization and ease of browsing in online fashion platforms. However, the two tools often operate independently, failing to combine the strengths of recommender systems to acc
Externí odkaz:
http://arxiv.org/abs/2207.12033
Publikováno v:
ACL2021
Mixed initiative in open-domain dialogue requires a system to pro-actively introduce new topics. The one-turn topic transition task explores how a system connects two topics in a cooperative and coherent manner. The goal of the task is to generate a
Externí odkaz:
http://arxiv.org/abs/2105.13710
We present a recurrent neural network based system for automatic quality estimation of natural language generation (NLG) outputs, which jointly learns to assign numerical ratings to individual outputs and to provide pairwise rankings of two different
Externí odkaz:
http://arxiv.org/abs/1910.04731