4 citations · 6 across the 8 of their papers we have counts for
Showing 2019Show all
2 papers · 1 filter
cs.CL2019★ 1 cited
On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation
Victor Prokhorov, Ehsan Shareghi, Yingzhen Li +2
Variational Autoencoders (VAEs) are known to suffer from learning uninformative latent representation of the input due to issues such as approximated posterior collapse, or entangl…
cs.CL2019
Generating Knowledge Graph Paths from Textual Definitions using Sequence-to-Sequence Models
Victor Prokhorov, Mohammad Taher Pilehvar, Nigel Collier
We present a novel method for mapping unrestricted text to knowledge graph entities by framing the task as a sequence-to-sequence problem. Specifically, given the encoded state of…