CSCI 5640 Natural Language Processing — Spring 2024

News

Information

Lectures
Monday, 10:30-12:15pm, Science Centre LG23 Tuesday, 16:30-17:15pm, Science Centre LG23
Tutorials
Tuesday, 17:30-18:15pm, Science Centre LG23
Instructor
Prof. Liwei WANG
Teaching Assistant
Yuntao Lu
Announcement
All updates will be sent to your emails. Please check your university emails.
Grading
Assignments + Paper Presentation + Final Project

Tutorial sessions would be the fastest and clearest way to discuss any problem. You are also welcomed to send emails to the instructor and the TAs.

Lectures

All related lecture materials will be posted on Blackboard → Lecture Notes.

The following schedule (tentative) are subject to minor modifications.

Lecture slide cannot be distributed outside the class.

Schedule
Week Date Topic Remark
1 Jan 8, 9 Intro & Basic Knowledge about NLP
2 Jan 15, 16 Neural Networks & Transformers
3 Jan 22, 23 Word and Word Vectors
4 Jan 29, 30 Language Modeling Release of Assignment 1
Complete team forming for projects
Assign selected paper to each team
5 Feb 5, 6 Pretrained Large Language Models: part 1
6 Feb 19, 20 Team Presentation on Selected Papers The week after Lunar New Year
Submission of Assignment 1
7 Feb 26, 27 Pretrained Large Language Models: part 2 Release of Assignment 2
Release of Final Project
8 Mar 4, 5 LLM applications Submission of Assignment 2
9 Mar 11, 12 RAG + LLMs Release of Assignment 3
10 Mar 18, 19 Language + Vision Submission of Assignment 3
11 Mar 25, 26 Understanding and Evaluations of Large Language Models
12 Apr 2 Frontiers Topics in NLP The day following Easter
13 Apr 8, 9 Final Projects Presentation (1)
14 Apr 15, 16 Final Projects Presentation (2) Submission of Final Project

Assignments

There will be three assignments and one paper presentation in total.

Final Project

More information about Final Project will be released later.

To maximize the project achievement, students should form teams of four in general. We recommend you using the same team as in paper presentation.

You are encouraged include in your report any illustrative, concrete examples that help you understand the papers you read.

Please submit your project report (in PDF) together with related codes and material online as a single zip file at blackboard.

Course Policy