Keeping Notes: Conditional Natural Language Generationwith a Scratchpad Mechanism
Table 4: Human evaluations show that the Scratchpad delivers a large improvement in both fluency and adequacy over Copynet and Coverage, accentuating the improvement in quantitative metrics (Bleu, Rouge, Meteor).
['Model', 'Fluency', 'Adequacy']
As the table shows, the judges assigned higher fluency and adequacy scores to our approach than both the coverage-based and copynet baseline. In the table we also report the fluency score of the gold questions as a way to measure the gap between the generated questions and the expected ones. Our approach is only 2 points behind the gold when it comes to generation fluency.