Recurrent Polynomial Network for Dialogue State TrackingThis work was supported by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning and the China NSFC project No. 61222208.
Table 2: Performance comparison between the RPN initialized by random values, and the RPN initialized by the CMBP coefficients on dstc2eval and dstc3eval.
['Initialization', 'dstc2eval Acc', 'dstc2eval L2', 'dstc3eval Acc', 'dstc3eval L2']
The performance of the RPN initialized by random values is compared with the performance of the RPN initialized by the integer-coefficient CMBP. Here, the CMBP has 12 non-zero coefficients and has the best performance on dstc2dev when trained on dstc2trn. This demonstrates the encoded prior knowledge and intuition in CMBP can be transferred to RPN to improve RPN’s performance, which is one of RPN’s advantage, bridging rule-based models and statistical models. In the rest of the experiments, all RPNs use CMBP coefficients for initialization.