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EN 601.764 Advanced NLP: Multilingual methods
Spring 2023
Tuesdays and Thursdays 1:30-2:45
Malone 228
Computer Science Department
Johns Hopkins University

This is a project based course focusing on the design and implementation of systems that scale Natural Language Processing methods beyond English. The course will cover both multilingual and cross-lingual methods with an emphasis on zero-shot and few-shot approaches, as well as ‘silver’ dataset creation. Modules will include Cross-Lingual Information Extraction & Semantics, Cross-Language Information Retrieval, Multilingual Question Answering, Multilingual Structured Prediction, Multilingual Automatic Speech Recognition, as well as other non-English centric NLP methods. Students will be expected to work in small groups and pick from one of the modules to create a model based on state-of-the-art methods covered in the class. The course will be roughly two-thirds lecture based and one-third students presenting project updates periodically throughout the semester.

Kenton Murray (
Office hours
By Appointment
Thursdays 3-4pm
Method of Instruction
The course will primarily be lecture and discussion based. Students will be expected to participate in active discussions of the course material. However, the majority of the instruction will be lectures and outside presentations. Students will be presenting project proposals, mid-point status updates, and final presentations.
Due to popular request, we will use Piazza at this link.
This is an upper-level graduate course. Readings will be provided by the instructor when necessary and may include technical reports, book chapter excerpts, journal and conference papers, etc. There is no required text book for the course.
Homework will be a range of coding exercises and short-form questions aimed at introducing students to the cutting-edge methods of multilingual natural language processing.
  • Four homework assignments (7.5% each)
  • Final project (50%)
  • Class Participation (20%)
Homework Schedule
There will be four homework assignments, tentative schedule:

All assignments are due at the start of class on the day they are due. Exceptions regarding tardiness will be considered on a case-by-case basis and must be submitted via e-mail 24 hours before the initial due date. Late submissions will be accepted using an exponential decay formula with a half-life of 1 week (604800 seconds).