1. The document discusses recent papers on deep learning techniques for text summarization, including neural attention models for sentence summarization and abstractive text summarization using sequence-to-sequence RNNs.
2. It also references papers on attention mechanisms in neural machine translation and mixture-of-experts models using sparsely-gated layers for scaling up neural networks.
3. The links provided relate to Wikipedia articles on deep learning and pointers to online resources for additional information on summarization techniques and recent papers in the field.