471 citations · 499 across the 3 of their papers we have counts for
8 papers
Label Semantic Aware Pre-training for Few-shot Text Classification
Aaron Mueller, Jason Krone, Salvatore Romeo +4
In text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification perfor…
Towards End-to-End In-Image Neural Machine Translation
Elman Mansimov, Mitchell Stern, Mia Chen +3
In this paper, we offer a preliminary investigation into the task of in-image machine translation: transforming an image containing text in one language into an image containing th…
Capturing document context inside sentence-level neural machine translation models with self-training
Elman Mansimov, Gábor Melis, Lei Yu
Neural machine translation (NMT) has arguably achieved human level parity when trained and evaluated at the sentence-level. Document-level neural machine translation has received l…
A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models
Elman Mansimov, Alex Wang, Sean Welleck +1
Undirected neural sequence models such as BERT (Devlin et al., 2019) have received renewed interest due to their success on discriminative natural language understanding tasks such…
Molecular geometry prediction using a deep generative graph neural network
Elman Mansimov, Omar Mahmood, Seokho Kang +1
A molecule's geometry, also known as conformation, is one of a molecule's most important properties, determining the reactions it participates in, the bonds it forms, and the inter…
Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement
Jason Lee, Elman Mansimov, Kyunghyun Cho
We propose a conditional non-autoregressive neural sequence model based on iterative refinement. The proposed model is designed based on the principles of latent variable models an…