Multi-Perspective Context Matching for Machine Comprehension
Table 3: Influence of the multi-perspective matching function in Eq.(5) .
['[ITALIC] l', 'EM', 'F1']
We also varied the number of perspectives l among {1, 10, 30, 50}, and kept the other options unchanged. We can see that, even if we only utilize one perspective, our multi-perspective matching function works better than the vanilla-cosine baseline. When increasing the number of perspectives, the performance improves significantly. Therefore, our multi-perspective matching function is really effective for matching vectors.