A Massive Collection of Cross-Lingual Web-Document Pairs
Table 4: Content-based Document Alignment Recall
['[BOLD] Method', '[BOLD] Low', '[BOLD] Mid', '[BOLD] High', '[BOLD] All']
Comparing DDE which directly applies LASER to the entirety of the document content, we see that performance is significantly lower than SAE which averages the individual sentence embeddings. We suspect this may be the case for two reasons (1) sentence encoders may suffer at representing the semantic meaning of long documents (2) there may be noisy boiler plate content at the beginning of each web document that is less useful semantically but dominates the representation. Intuitively, higher-resource directions appear to align better than lower-resource directions. We believe this is a byproduct of the data LASER was trained on which is predominantly high-resource.