activity
20162020
most citedLingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

184 citations · 242 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG20207 cited

Insertion-Deletion Transformer

Laura Ruis, Mitchell Stern, Julia Proskurnia +1

We propose the Insertion-Deletion Transformer, a novel transformer-based neural architecture and training method for sequence generation. The model consists of two phases that are…

math.LO2019

The Destruction of the Axiom of Determinacy by Forcings on when is Regular

William Chan, Stephen Jackson

proves that for all nontrivial forcings on a wellorderable set of cardinality less than , . $…

math.LO20192 cited

Cardinality of Wellordered Disjoint Unions of Quotients of Smooth Equivalence Relations

William Chan, Stephen Jackson

Assume . Let denote the relation of being in bijection. Let and be a se…

cs.LG2019184 cited

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Jonathan Shen, Patrick Nguyen, Yonghui Wu +88

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…

cs.CL201610 cited

Very Deep Convolutional Networks for End-to-End Speech Recognition

Yu Zhang, William Chan, Navdeep Jaitly

Sequence-to-sequence models have shown success in end-to-end speech recognition. However these models have only used shallow acoustic encoder networks. In our work, we successively…

stat.ML201637 cited

Latent Sequence Decompositions

William Chan, Yu Zhang, Quoc Le +1

We present the Latent Sequence Decompositions (LSD) framework. LSD decomposes sequences with variable lengthed output units as a function of both the input sequence and the output…