CSE 599 D1:
Advanced Natural Language Processing- Spring 2019 Wed, Fri
1:30-2:50 pm in Gates 271 |
Instructor: Hanna Hajishirzi (Paul Allen Center 470) (hannaneh at washington dot edu) Office hours: by appointment |
TA: Dae Lee (dhlee4 at uw dot edu) Office hours: by appointment |
Course
Objectives
This advanced course deeply explores important topics in NLP. The objective of this class is to enhance students' knowledge about current techniques, challenges, and developments in different areas of NLP; to encourage discussions and collaborations among students; to improve students' analytical thinking and creativity; and to improve presentation and writing skills. In this class, students are required to read, think, present, and write intensively.
Theme:
Representation and Reasoning in NLP
This course will be concentrated on knowledge representation and reasoning in NLP, including semantic representations, knowledge acquisition, question answering, and reasoning. The goal is to acquire comprehensive understanding and insights into the emerging developments and challenges of these advanced topics, and to develop future research directions and original research ideas.
Class
Activities and Evaluation
Students will be evaluated based on these four activities (% of final grade):
(i) leading class discussions (30%),
(ii) participation in the discussions (25%),
(iii) paper review (15%),
(iv) research proposal, in which each student proposes an original research project (30%).
(Optional) students can optionally pursue a research project which will contribute toward additional 25% grade.
Prerequisite
and Background Material
This advanced course deeply explores important topics in NLP. It is assumed that participants have taken CSE 517, are familiar with the fundamental ideas in NLP, and pursue research in NLP or related fields. Here are some pointers for background materials.
● UW-NLP CSE517 [here]
● NLP textbooks:
○ D. Jurafsky & James H. Martin, Speech and Language Processing: n Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition, Prentice Hall, Second Edition, 2009
○ C.D. Manning & H. Schuetze, Foundations of Statistical Natural Language Processing, Cambridge: MIT Press, 1999 (available online, free if accessed from UW computers)
Click here for potential papers for class discussions.
Schedule
Paper
Review
We will provide the list of papers for the
paper report. Check here
for instructions for paper review. The paper review should not be longer than 2
pages. Deposit the paper review to the dropbox.
Also, to see some more samples for paper reviews you can check the open review website https://openreview.net. For example, these are sample reviews from the most recent ICLR conference: https://openreview.net/group?id=ICLR.cc/2019/Conference
Research
Proposal
Write a 4-page research proposal paper describing a line of research in NLP. The research proposal should be about a new project that would extend a clearly identified past research contribution. The research proposal should:
● Build upon or extend what was done in the past work;
● Address challenges or weaknesses in the past research;
● Propose logical extensions or next steps to the focus research; and
● Describe a possible evaluation methodology, experimental design, and required evaluation resources.
You can find some guidelines in the link, or schedule a meeting with the instructor or the TA to learn more.
The 4-page limit is a hard constraint and will be enforced seriously. References don't count toward the page limit. Please use the ACL 2019 style files without modification.
Submit the research proposal to the Dropbox.
Course
Administration and Policies
● Assignments should be done individually unless otherwise specified. You are expected to maintain the utmost level of academic integrity in the course.
●
Late Policy: Each student has SEVEN PENALTY-FREE DAY FOR THE WHOLE QUARTER(**UPDATED 25 APR 2019**),
other than that any late submission will be penalized at a penalty of 10% of
the maximum grade per day.
Communication
● If you have comments of general interest, please use the discussion forum. Please consider posting your questions there; everyone will benefit. We also encourage you to try to answer questions, which will count as class participation. We will monitor daily and contribute as long as the boards are being used.
● We appreciate feedback throughout the quarter -- you can submit feedback through the Allen School's anonymous feedback tool
● Submit assignments to the dropbox