A
Ashish Vaswani
Researcher at Google
Publications - 73
Citations - 70493
Ashish Vaswani is an academic researcher from Google. The author has contributed to research in topics: Machine translation & Transformer (machine learning model). The author has an hindex of 34, co-authored 70 publications receiving 35599 citations. Previous affiliations of Ashish Vaswani include Information Sciences Institute & University of Southern California.
Papers
More filters
Proceedings ArticleDOI
Supertagging With LSTMs
TL;DR: This paper presents new state-of-the-art performance on CCG supertagging and parsing and demonstrates that while feed-forward architectures can compete with bidirectional LSTMs on POS tagging, models that encode the complete sentence are necessary for the long range syntactic information encoded in supertags.
Patent
Fast decoding in sequence models using discrete latent variables
Posted Content
Music Transformer
Cheng-Zhi Anna Huang,Ashish Vaswani,Jakob Uszkoreit,Noam Shazeer,Ian Simon,Curtis Hawthorne,Andrew M. Dai,Matthew D. Hoffman,Monica Dinculescu,Douglas Eck +9 more
TL;DR: It is demonstrated that a Transformer with the modified relative attention mechanism can generate minute-long compositions with compelling structure, generate continuations that coherently elaborate on a given motif, and in a seq2seq setup generate accompaniments conditioned on melodies.
Posted Content
Theory and Experiments on Vector Quantized Autoencoders
TL;DR: This work investigates an alternate training technique for VQ-VAE, inspired by its connection to the Expectation Maximization (EM) algorithm, and develops a non-autoregressive machine translation model whose accuracy almost matches a strong greedy autoregressive baseline Transformer, while being 3.3 times faster at inference.
Journal ArticleDOI
Decoding the neural representation of story meanings across languages.
Morteza Dehghani,Reihane Boghrati,Kingson Man,Joe Hoover,Sarah I. Gimbel,Ashish Vaswani,Jason D. Zevin,Mary Helen Immordino-Yang,Andrew S. Gordon,Antonio R. Damasio,Jonas T. Kaplan +10 more
TL;DR: This work exposed English, Mandarin, and Farsi native speakers to native language translations of the same stories during fMRI scanning to demonstrate that neuro‐semantic encoding of narratives happens at levels higher than individual semantic units and that this encoding is systematic across both individuals and languages.