Augmented Seq2seq

• [x] Vanilla Seq2seq
• [x] Conditioning decoder on external context
  • [x] Dynamic Decoder (teacher forcing removed)
• [x] Language Modeling with encoder
• [x] Bidirectional encoder
• [ ] RNNSearch : Soft Alignment
• [ ] Multi-turn Conversation Modeling with Hierarchical Recurrent Encoder-Decoder (HRED)
• [ ] Memory augmentation

Reference

1. Ed Grefenstette, Beyond Sequence to Sequence with Augmented RNNs video, slides
2. Neural Machine Translation by Jointly Learning to Align and Translate
3. End-to-End Memory Networks
4. Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
5. Advanced Seq2seq in tensorflow
6. Beam Search
7. Multi-task Learning in tensorflow
8. Enhanced Attention-based Encoder-Decoder model for NMT

Credits

• thank you @ematvey, for helping me understand raw_rnn