DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue
Table 3: Human evaluation of 100 sample responses on VisDial v1.0 validation set. M1: percentage of responses that pass the Turing Test. M2: percentage of responses that are evaluated better or equal to human responses. Repetition: percentage of responses that have meaningless repeated words. Richness: percentage of responses that contain detailed content to answer the question.
['Model', 'M1 ↑', 'M2 ↑', 'Repetition↓', 'Richness ↑']
Distinct from previous works, we add Repetition and Richness metrics, and for all metrics, we record the score when at least 2 persons agree. After incorporating RSL and Memory Unit with WDL, the repetition further reduces by 0.06 while M1 and M2 outperform by 0.06 and 0.07 respectively, which proves the complementary advantages between these two level information. We also notice that Richness decreases slightly. This is mainly because the information from RSL concentrates more attention on the global information, rather than detailed information.