83 citations · 100 across the 4 of their papers we have counts for
5 papers
Generation Challenges: Results of the Accuracy Evaluation Shared Task
Craig Thomson, Ehud Reiter
The Shared Task on Evaluating Accuracy focused on techniques (both manual and automatic) for evaluating the factual accuracy of texts produced by neural NLG systems, in a sports-re…
Towards objectively evaluating the quality of generated medical summaries
Francesco Moramarco, Damir Juric, Aleksandar Savkov +1
We propose a method for evaluating the quality of generated text by asking evaluators to count facts, and computing precision, recall, f-score, and accuracy from the raw counts. We…
A preliminary study on evaluating Consultation Notes with Post-Editing
Francesco Moramarco, Alex Papadopoulos Korfiatis, Aleksandar Savkov +1
Automatic summarisation has the potential to aid physicians in streamlining clerical tasks such as note taking. But it is notoriously difficult to evaluate these systems and demons…
Natural Language Generation Challenges for Explainable AI
Ehud Reiter
Good quality explanations of artificial intelligence (XAI) reasoning must be written (and evaluated) for an explanatory purpose, targeted towards their readers, have a good narrati…
Acquiring Correct Knowledge for Natural Language Generation
E. Reiter, R. Robertson, S. G. Sripada
Natural language generation (NLG) systems are computer software systems that produce texts in English and other human languages, often from non-linguistic input data. NLG systems,…