Multi-Source Domain Adaptation with Mixture of Experts
Table 6: POS tagging accuracy with varying amounts of Twitter data in training.
['Target', 'Model (∗ [BOLD] -A)', '# Twitter instances 750', '# Twitter instances 1,500', '# Twitter instances 2,250']
We further study the impact of this outlier source by varying the amount of Twitter data used during training. We gradually increase the number of Twitter instances by 750. However, the performance of our MoE (MoE-A) model stays stable, consistently increasing with more Twitter, showing robustness in handling negative transfer.