Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
Table 6: Hyper-parameter selection for the full pipeline system. h and k are the retrieval filtering hyper-parameters mentioned in the main paper. P-level and S-level indicate paragraph-level and sentence-level respectively. “{}” means values enumerated from a set. “[]” means values enumerated from a range with interval=0.1 “BS.”=Batch Size “# E.”=Number of Epochs
['Module', 'BS.', '# E.', '[ITALIC] k', '[ITALIC] h']
Fact Verification: The input format is the same as that of semantic retrieval and the objective is Jver=−∑iyi⋅log(^yi), where ^yi∈R3 denotes the model’s output for the three verification labels, and yi is a one-hot embedding for the ground-truth label. For verifiable queries, we used ground truth evidential sentences plus some other sentences sampled from upstream retrieved set as new evidential context for NLI. For non-verifiable queries, we only used sentences sampled from upstream retrieved set as context because those queries are not associated with ground truth evidential sentences. Additional training details and hyper-parameter selections are in the Appendix (Sec. The hyper-parameters were chosen based on the performance of the system on the dev set.