Explore document-level models in natural language processing through this comprehensive lecture from Carnegie Mellon University's Neural Networks for NLP course. Delve into topics such as language modeling, long-term dependencies, topic modeling, and coreference resolution. Learn about entity mention models, entity-centric models, and complex features in coreference. Examine discourse parsing techniques, including shift-reduce parsers and recursive models. Understand the importance of coreference in language modeling and its applications in discourse analysis. Investigate document classification methods and their accuracy. Gain insights into advanced NLP concepts and techniques for processing and analyzing entire documents.