NeuralDialogPapers

Why we included this project

For anyone getting into neural dialogue systems, this is a well-organized reading list that maps the field from the ground up. Papers are grouped into task-oriented bots and open-domain chat bots, with sub-sections for user simulators, reinforcement learning, retrieval methods, and diversity, so you can follow a coherent thread instead of stumbling through scattered arXiv links. The list was curated by Tiancheng Zhao, a researcher who worked on dialogue at CMU, which gives the selections real authority. It works well as a study companion for graduate students or engineers who want to understand how modern conversational AI evolved, since the papers trace the progression from early end-to-end models to later negotiation and knowledge-grounded systems. Because it is a paper index rather than runnable code, treat it as a research map to guide your reading, not something to deploy.