Latest research advances on semantic slot filling.
This repo mainly summary latest research advances on semantic slot filling.
Thank you pay attention to the repo and it will not be updated!
Model | F1 Score | Intent Accuracy | Year |
---|---|---|---|
Recursive NN | 0.9396 | 0.954 | Guo et al. 2014 |
Joint model with recurrent intent and slot label context | 0.9447 | 0.984 | Liu and Lane, 2016b |
Joint model with recurrent slot label context | 0.9464 | 0.984 | Liu and Lane, 2016b |
RNN with Label Sampling | 0.9489 | NA | Liu and Lane, 2015 |
Hybrid RNN | 0.9506 | NA | Mesnil et al., 2015 |
RNN-EM | 0.9525 | NA | Peng and Yao, 2015 |
CNN-CRF | 0.9435 | NA | Xu and Sarikaya, 2013 |
Encoder-labeler Deep LSTM | 0.9566 | NA | Kurata et al., 2016 |
Joint GRU model(W) | 0.9549 | 0.9810 | Zhang and Wang, 2016 |
Attention Encoder-Decoder NN | 0.9587 | 0.9843 | Liu and Lane, 2016a |
Bi-model without a decoder | 0.9665 | 0.9876 | Wang and Shen, 2018 |
Bi-model with a decoder | 0.9689 | 0.9899 | Wang and Shen, 2018 |