3 papers
cs.CL2020
Generating Label Cohesive and Well-Formed Adversarial Claims
Pepa Atanasova, Dustin Wright, Isabelle Augenstein
Adversarial attacks reveal important vulnerabilities and flaws of trained models. One potent type of attack are universal adversarial triggers, which are individual n-grams that, w…
cs.LG2020
Transformer Based Multi-Source Domain Adaptation
Dustin Wright, Isabelle Augenstein
In practical machine learning settings, the data on which a model must make predictions often come from a different distribution than the data it was trained on. Here, we investiga…
cs.SD2018
Rethinking Recurrent Latent Variable Model for Music Composition
Eunjeong Stella Koh, Shlomo Dubnov, Dustin Wright
We present a model for capturing musical features and creating novel sequences of music, called the Convolutional Variational Recurrent Neural Network. To generate sequential data,…