Explore document-level natural language processing models in this lecture from CMU's Neural Networks for NLP course. Dive into coreference resolution techniques, including mention pair, entity-mention, and ranking models. Examine discourse parsing approaches and document-level prediction tasks. Learn about error analysis in coreference systems and recent advances using deep reinforcement learning and end-to-end neural models. Discover how attention-based hierarchical neural networks can be applied to discourse parsing. Gain insights into document-level challenges like discourse unit prediction and story completion tasks.