no code implementations • EMNLP 2020 • Henry Elder, Alexander O{'}Connor, Jennifer Foster
Neural Natural Language Generation (NLG) systems are well known for their unreliability.
no code implementations • MSR (COLING) 2020 • Henry Elder
In this paper, we describe the ADAPT submission to the Surface Realization Shared Task 2020.
1 code implementation • ACL 2020 • Henry Elder, Robert Burke, Alexander O'Connor, Jennifer Foster
The Surface Realization Shared Tasks of 2018 and 2019 were Natural Language Generation shared tasks with the goal of exploring approaches to surface realization from Universal-Dependency-like trees to surface strings for several languages.
no code implementations • WS 2019 • Henry Elder, Jennifer Foster, James Barry, Alexander O'Connor
Generated output from neural NLG systems often contain errors such as hallucination, repetition or contradiction.
no code implementations • WS 2018 • Henry Elder, Sebastian Gehrmann, Alex O{'}Connor, er, Qun Liu
In natural language generation (NLG), the task is to generate utterances from a more abstract input, such as structured data.
1 code implementation • WS 2018 • Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, Alexander M. Rush
Learning to generate fluent natural language from structured data with neural networks has become an common approach for NLG.
no code implementations • WS 2018 • Henry Elder, Chris Hokamp
This work presents a new state of the art in reconstruction of surface realizations from obfuscated text.