How to use additional input features for Abstractive summarization? Seq2Seq
Hello All,I am trainning a length controlled abstractive summarizer and I would like to add the length of the golden summary as an additional feature for the model to learn the desired length. I saw the answerherefor classification in which a numeric feature is added to the hidden state of the [CLS] token. Since my problem is Seq2Seq language generation, does anyone have an idea on how to add this extra feature?I understand it should be added to the decoder which is the one generating the output, but if you guys know a better way or if Im incorrect please let me know.Best regards,