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cs.CL2019
Learning Dense Representations for Entity Retrieval
Daniel Gillick, Sayali Kulkarni, Larry Lansing +4
We show that it is feasible to perform entity linking by training a dual encoder (two-tower) model that encodes mentions and entities in the same dense vector space, where candidat…
cs.CL2016
Globally Normalized Transition-Based Neural Networks
Daniel Andor, Chris Alberti, David Weiss +5
We introduce a globally normalized transition-based neural network model that achieves state-of-the-art part-of-speech tagging, dependency parsing and sentence compression results.…