activity
20162020
most citedDiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion

18 citations · 18 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CL2020

Semantically Driven Sentence Fusion: Modeling and Evaluation

Eyal Ben-David, Orgad Keller, Eric Malmi +2

Sentence fusion is the task of joining related sentences into coherent text. Current training and evaluation schemes for this task are based on single reference ground-truths and d…

cs.CL2020

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…

cs.CL2020

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…

cs.CL2019

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…

cs.CL201918 cited

DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion

Mor Geva, Eric Malmi, Idan Szpektor +1

Sentence fusion is the task of joining several independent sentences into a single coherent text. Current datasets for sentence fusion are small and insufficient for training moder…

cs.CV2017

Domain Adaptation for Resume Classification Using Convolutional Neural Networks

Luiza Sayfullina, Eric Malmi, Yiping Liao +1

We propose a novel method for classifying resume data of job applicants into 27 different job categories using convolutional neural networks. Since resume data is costly and hard t…