Spring 2022 - CMPT 983 G100
Special Topics in Artificial Intelligence (3)
Class Number: 5549
Delivery Method: In Person
A seminar-oriented course covering topics at the intersection of language, vision, graphics, and robotics. The class focuses on the grounding of language to various representations and modalities. For topics covered in Spring 2021 (see https://angelxuanchang.github.io/cmpt983-sp2021/). The format of the class will be a mix of lectures and student-led presentations. Students are expected to have prior experience with deep learning concepts and framework (Pytorch, Tensorflow, etc), and should also have familiarity with one of the areas of natural language processing, vision, graphics or robotics. Each week, students will read papers in a particular area of language grounding, and discuss the contributions, limitations and interconnections between the papers. Students will also work on a research project during the course, culminating in a final presentation and written report. The course aims to provide practical experience in comprehending, analyzing and synthesizing research in grounded natural language understanding. Note: This course is NOT an introductory course to natural language processing. If you are interested in learning about natural language processing, CMPT 413/713 is offered in the fall.
- Multimodal embeddings and contrastive learning
- Pre-training for multimodal grounding
- Grounding of language to machine interpretable programs (semantic parsing)
- Visual grounding of language and tasks (captioning, VQA models, referring expressions)
- Interpretation of language commands for embodied navigation and interaction
- Interactive language learning through language games and dialogue
- Grounded knowledge representations for mapping language to the 3D world
- Generative models for content creation from text
- Grounded language acquisition and understanding
Based on paper critiques, presentations, and class project.
Graduate Studies Notes:
Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
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TEACHING AT SFU IN SPRING 2022
Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place. Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes. You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).
Enrolling in a course acknowledges that you are able to attend in whatever format is required. You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.
Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (firstname.lastname@example.org or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.