46 citations · 123 across the 7 of their papers we have counts for
16 papers
Controlled Text Generation as Continuous Optimization with Multiple Constraints
Sachin Kumar, Eric Malmi, Aliaksei Severyn +1
As large-scale language model pretraining pushes the state-of-the-art in text generation, recent work has turned to controlling attributes of the text such models generate. While m…
Unsupervised Text Style Transfer with Padded Masked Language Models
Eric Malmi, Aliaksei Severyn, Sascha Rothe
We propose Masker, an unsupervised text-editing method for style transfer. To tackle cases when no parallel source-target pairs are available, we train masked language models (MLMs…
Felix: Flexible Text Editing Through Tagging and Insertion
Jonathan Mallinson, Aliaksei Severyn, Eric Malmi +1
We present Felix --- a flexible text-editing approach for generation, designed to derive the maximum benefit from the ideas of decoding with bi-directional contexts and self-superv…
Encode, Tag, Realize: High-Precision Text Editing
Eric Malmi, Sebastian Krause, Sascha Rothe +2
We propose LaserTagger - a sequence tagging approach that casts text generation as a text editing task. Target texts are reconstructed from the inputs using three main edit operati…
Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities
Octavian-Eugen Ganea, Sylvain Gelly, Gary Bécigneul +1
The Softmax function on top of a final linear layer is the de facto method to output probability distributions in neural networks. In many applications such as language models or t…
Adversarial Neural Networks for Cross-lingual Sequence Tagging
Heike Adel, Anton Bryl, David Weiss +1
We study cross-lingual sequence tagging with little or no labeled data in the target language. Adversarial training has previously been shown to be effective for training cross-lin…