This is the official implementation of our AAAI-21 accepted paper Label Confusion Learning to Enhance Text Classification Models.
The structure of LCM looks like this:
Here we provide some demo experimental code & datasets.
python 3.6 tensorflow 2.2.0 keras 2.3.1
LCM-based LSTM:
Run python lcm_exp_on_lstm.py to compare the performance of LSTM, LSTM with label smoothing(LS) and LSTM with LCM.
LCM-based BERT:
Run python lcm_exp_on_bert.py to compare the performance of BERT, BERT with label smoothing(LS) and BERT with LCM.
The final results will be outputted to output/ directory.
The curve below shows our results on 20NG with LSTM as basic predictor. By changing the α, we can control the influence of LCM on the original model.
