Generate, Delete and Rewrite: A Three-Stage Framework for Improving Persona Consistency of Dialogue Generation
Table 5: Results of the ablation study. GDR is significantly better than the ablated approaches, with an only exception marked by ‡.
['[BOLD] Model', '[BOLD] Const.', '[BOLD] Fluc.', '[BOLD] Relv.', '[BOLD] Info.', '[BOLD] PPL']
First, we look into which components contribute to the consistency. As seen, from T, G, GR to GDR, every step has an observable improvement in Const., indicating the effectiveness of our model’s design. Both the tuple-interaction in G and the rewriting process in R contribute to the improvements of persona consistency. The GRdR approach, with nothing different from GDR but a random deleting strategy, serves as a foil to our GDR model, which indicates a well-learned consistency matching model is of great benefit to our three-stage generation framework to generate persona consistent dialogues.