Bidirectional LSTM

[TinaB19]

I tried to use bidirectional lstm with merge_mode='sum' for encoding, but when I try to predict headlines, the model barely generates anything; However, the loss is lower than when I use the simple lstm. This is the only change that I made. Do you know why this happens?

[udibr]

generating with BiLSTM is tricky. In generation you move forward step by step generating one word at a time. However the BiLSTM model requires you to move both forward and backward.

If you want to use BiLSTM you can use it on the steps that are running over the article content and then run just a forward LSTM on the headline so latter you can generate your own headline from this forward only pass

[TinaB19]

Can this be done by changing the current model? Considering that you feed both description and headline as input to a same model? I tried to do it myself but had no luck.