410 citations · 964 across the 27 of their papers we have counts for
4 papers · 1 filter
Adversarial Neural Networks for Cross-lingual Sequence Tagging
Heike Adel, Anton Bryl, David Weiss +1
We study cross-lingual sequence tagging with little or no labeled data in the target language. Adversarial training has previously been shown to be effective for training cross-lin…
On Accurate Evaluation of GANs for Language Generation
Stanislau Semeniuta, Aliaksei Severyn, Sylvain Gelly
Generative Adversarial Networks (GANs) are a promising approach to language generation. The latest works introducing novel GAN models for language generation use n-gram based metri…
Prosody Modifications for Question-Answering in Voice-Only Settings
Aleksandr Chuklin, Aliaksei Severyn, Johanne Trippas +3
Many popular form factors of digital assistants---such as Amazon Echo, Apple Homepod, or Google Home---enable the user to hold a conversation with these systems based only on the s…
Eval all, trust a few, do wrong to none: Comparing sentence generation models
Ondřej Cífka, Aliaksei Severyn, Enrique Alfonseca +1
In this paper, we study recent neural generative models for text generation related to variational autoencoders. Previous works have employed various techniques to control the prio…