12 citations · 23 across the 3 of their papers we have counts for
4 papers
Disembodied Machine Learning: On the Illusion of Objectivity in NLP
Zeerak Waseem, Smarika Lulz, Joachim Bingel +1
Machine Learning seeks to identify and encode bodies of knowledge within provided datasets. However, data encodes subjective content, which determines the possible outcomes of the…
Domain Transfer in Dialogue Systems without Turn-Level Supervision
Joachim Bingel, Victor Petrén Bach Hansen, Ana Valeria Gonzalez +3
Task oriented dialogue systems rely heavily on specialized dialogue state tracking (DST) modules for dynamically predicting user intent throughout the conversation. State-of-the-ar…
Latent Multi-task Architecture Learning
Sebastian Ruder, Joachim Bingel, Isabelle Augenstein +1
Multi-task learning (MTL) allows deep neural networks to learn from related tasks by sharing parameters with other networks. In practice, however, MTL involves searching an enormou…
Identifying beneficial task relations for multi-task learning in deep neural networks
Joachim Bingel, Anders Søgaard
Multi-task learning (MTL) in deep neural networks for NLP has recently received increasing interest due to some compelling benefits, including its potential to efficiently regulari…