DSReg: Using Distant Supervision as a Regularizer
Table 3: Performances of different models on the text classification task.
['Model', 'SST', 'Hotel Review', 'Financial Statement']
S4SS1SSS0Px4 As can be seen, three versions of the proposed DSReg models, i.e., L1+L2, L1+L3 and L1+L2+L3, outperform the binary classification model and the pipelined model, which aligns with our expectation. For the pipelined model, since the error accumulates over stages, it underperforms not only the DSReg models, but also the binary classification model. By using both the three-class classification (L3) and Pos∪HardNeg|EasyNeg (L2) as regulations, the L1+L2+L3 setting leads to the best performance.