22 citations · 29 across the 10 of their papers we have counts for
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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.LG2019★ 22 cited
Explaining Deep Classification of Time-Series Data with Learned Prototypes
Alan H. Gee, Diego Garcia-Olano, Joydeep Ghosh +1
The emergence of deep learning networks raises a need for explainable AI so that users and domain experts can be confident applying them to high-risk decisions. In this paper, we l…