Canvas: https://canvas.ubc.ca/courses/130179
Piazza: https://piazza.com/ubc.ca/winterterm22023/cpsc532v/
Time: Term 2 (Jan-Apr 2023), MW 3:00-4:30
Location: SWNG 105
Instructor: Vered Shwartz	Office hours: By appointment, contact through Canvas
TA: Sahithya Ravi	Office hours: By appointment

Natural language processing (NLP) is a growing field within artificial intelligence. The fundamental goal of NLP is to program computers capable of human-level understanding of natural language. Common NLP applications include personal assistants and chatbots, automatic translation, question answering, sentiment analysis and summarization. Among the main challenges of NLP research is that human language is often ambiguous and underspecified. A person processing language relies heavily on their commonsense knowledge and reasoning abilities to resolve these ambiguities and complete missing information. Machine learning based NLP models, on the other hand, lack this commonsense and often make absurd mistakes. In this course, we will discuss the various topics, including the following:

• What is commonsense and why do we need it in NLP? How does it relate to earlier attempts in AI to teach machines commonsense?
• How do we measure commonsense reasoning abilities? How good are our existing models?
• How can commonsense be acquired? What are the many challenges in acquiring commonsense knowledge?
• How can we incorporate such knowledge into NLP models?
• Can we teach computers to reason?

The course assumes you have an understanding of machine learning and deep learning, and basic familiarity with NLP. If you haven't taken a previous NLP course, I will refer you to online tutorials. The course will involve attending class, reading, presenting, and discussing papers, two homework assignments, and a research project on an idea you are passionate about in this space.

Project	proposal, report, and final presentation (in groups)	40%
Assignments	2 assignments, 20% each (in groups)	40%
Paper Presentations	presenting one research paper (individually)	20%

The project will be done in groups of 2-3. You may choose any research problem related to the course topics. You will be required to:

1. Submit a written project proposal, describing the research problem, existing literature, the data and methods you will use, how you plan to evaluate your method (if applicable), and a proposed timeline.
2. Submit a written final project report.
3. Present the final project presentation to the class.

Details on the different tasks will be published on Canvas.

The course will have two assignments. They will be published on Canvas.

Each student will be assigned one research paper and a role:

1. Presenter. Give a 10 minute oral description of the highlights of the paper.
2. Peer Reviewer x 3. Pretend the paper was submitted to a top-tier NLP conference, and complete a full review of the paper, including recommending whether to accept or reject the paper. Present it in class (5 min each).
3. Meta-reviewer. Your job is to concisely summarize the reasons to accept or reject the paper based on the reviews and discussion in class. Present it in class (5 min).
4. Researcher. You’re a researcher who is working on a new project in this area. Propose an imaginary follow-up project. Present it in class (<10 min).

The group of students working on each paper will create, present, and submit one slide deck.