Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems
Table 2: Comparison of MTN (Base) to state-of-the-art visual dialogue models on the test-std v1.0. The best measure is highlighted in bold.
['[BOLD] Model', '[BOLD] NDCG']
We evaluate our model with Normalized Discounted Cumulative Gain (NDCG) score by submitting the predicted ranks of the response candidates to the evaluation server (as the ground-truth for the test-std v1.0 split is not published). We keep all the training procedures unchanged from the video-grounded dialogue task. It is interesting that our generative model outperforms other retrieval-based approaches in NDCG without any task-specific fine-tuning.