LIN 393

Natural Language Generation

The University of Texas at Austin
Fall 2022
Instructor: Jessy Li



Course Information

Course Description

Text generation is an exciting area of natural language processing, where modern approaches utilize large-scale pre-trained models for summarization, dialog generation, text simplification, machine translation, creative writing, etc. And yet, it also comes with a number of challenges: How do we generate text that is linguistically well-structured and factually correct? How do we understand model behavior when on the surface everything’s so black-boxed? How do we gauge the quality of generated text? Do models make ethical decisions and if not, how do we fix them? In this seminar, we explore the above questions to gain a deeper understanding of the field.


Graduate standing. Prior coursework in Computational Linguistics/Natural Language Processing/Machine Learning/a related field in AI, or instructor consent.


There will be no textbook for this seminar; reading material will consists of technical papers discussed in each meeting.

Organization and Content

Grading Policy

Extension Policy

All extensions will be negotiated on a case-by-case basis. You must talk to the instructor before the deadline in question. If you did not obtain a permission on extension, then by default, 10 points (out of 100) will be deducted for lateness, plus an additional 5 point for every 24-hour period beyond 2 that the assignment is late.

Academic Dishonesty Policy

You are encouraged to discuss assignments with classmates. But all written work must be your own. Students caught cheating will automatically fail the course. If in doubt, ask the instructor.

Notice about students with disabilities

The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. Please contact the Division of Diversity and Community Engagement, Services for Students with Disabilities.

Notice about missed work due to religious holy days

A student who misses an examination, work assignment, or other project due to the observance of a religious holy day will be given an opportunity to complete the work missed within a reasonable time after the absence, provided that he or she has properly notified the instructor. It is the policy of the University of Texas at Austin that the student must notify the instructor at least fourteen days prior to the classes scheduled on dates he or she will be absent to observe a religious holy day. For religious holy days that fall within the first two weeks of the semester, the notice should be given on the first day of the semester. The student will not be penalized for these excused absences, but the instructor may appropriately respond if the student fails to complete satisfactorily the missed assignment or examination within a reasonable time after the excused absence.