| Algorithm Model | Composition |
| BiDAF Model | · Two bidirectional LSTM layers · Self-attention mechanism · Global attention mechanism · Predict the start and end positions of the answer |
| R-Net Model | · Three bidirectional LSTM layers · Bitwise attention mechanism · Gated recurrent unit · Predict the start and end positions of the answer |
| XLNet Model | · Neural network architecture based on Transformer · Use autoregressive mechanism to predict answers · Permutation-based language model |