604 citations · 2.5k across the 63 of their papers we have counts for
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Bayesian Compression for Natural Language Processing
Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry Vetrov
In natural language processing, a lot of the tasks are successfully solved with recurrent neural networks, but such models have a huge number of parameters. The majority of these p…
Conditional Generators of Words Definitions
Artyom Gadetsky, Ilya Yakubovskiy, Dmitry Vetrov
We explore recently introduced definition modeling technique that provided the tool for evaluation of different distributed vector representations of words through modeling diction…
Breaking Sticks and Ambiguities with Adaptive Skip-gram
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin +1
Recently proposed Skip-gram model is a powerful method for learning high-dimensional word representations that capture rich semantic relationships between words. However, Skip-gram…