CS 6741: Topics in Natural Language Processing and Machine Learning (Fall 2021)

Robust autonomous language reasoning has the potential to transform how we interact with computers and study language at scale. Building systems that understand and generate natural language provides avenues for both new applications and better understanding of language itself.

This is a research-first course. We will focus on 2–3 cutting-edge research topics through paper readings and discussions. We will use an experimental role-playing format for discussions. The guidelines outline the course format, and provide advice for our reading process. The topics for fall 2021 are: (a) cognitive science and NLP, (b) bandit learning and NLP, and (c) language grounding. We will take a very broad view of these topics. The schedule provides a tentative list of papers. We will potentially also host invited speakers for talks.

The course also includes a research project component due at the end of the semester. The topic for the project will be determined in discussion between the student and the instructor to balance the student’s interests, current research, and the course topics. Students who already took the class in the past and wish to re-take it, may take the class without submitting a project for an S/U grade. This requires instructor permission, so please obtain it in advance.

Acknowledgements: we thank Robert Hawkins and Dipendra Misra for reading recommendations.