Course Policies
Collaboration
Collaboration is strongly encouraged, both in this course and in the profession of NLP. Please make sure you adhere to the following guidelines.
Homework Assignments
You may discuss the homework assignments with anyone at any time, but you must ultimately complete and write up the assigned work for yourself.
Reading Quizzes
You are strongly encouraged to discuss the readings with your peers before the reading quizzes open, but you may not discuss the readings or quiz questions with anyone while the quizzes are open.
Project
Projects should be completed in groups of three or four, which should be formed by the time the full proposal is submitted.
Academic Integrity
Work you submit should be your own. Please consult the GSAS Statement on Academic Integrity for more information. Penalties for violations of academic integrity may include failure of the course, suspension from the University, or even expulsion.
Please follow these guidelines in order to avoid plagiarism.
Citations
All text and figures from an outside source, as well as descriptions or other depictions of baseline models and datasets, must be cited according to ACL guidelines.
Reusing code
All code submitted for homework assignments must be your own. You may reuse code submitted by others for the final project, but all such reused code must be cited in your paper.
Violations of this policy will result in a zero grade for the submitted work and a referral to the University for further investigation.
Use of Generative AI Tools
Use of generative AI tools such as ChatGPT to aid with coursework is permitted, as long as these tools only generate text output (including code). For instance, you are allowed to use ChatGPT with a GPT-3.5 backend to help you generate code or improve your writing, but you are not allowed to incorporate figures generated using DALL-E. Usage of generative AI tools is subject to applicable NYU policies.
Homework Assignments
When using generative AI tools on homework assignments, you are required to provide a full transcript of all interactions (prompts and responses) between you and the generative AI tool in the form of a .txt file. Specific instructions for this will be provided in each assignment.
Final Paper
Use of generative AI tools on the final paper draft and the final paper is subject to the Association for Computational Linguistics Policy on AI Writing Assistance.
Respectful, Inclusive, and Productive Participation
The field of NLP is a diverse, international community that benefits from incorporating a wide variety of different perspectives. All members of the class, both students and members of course staff, are expected to foster an inclusive and productive environment by treating one another with civility and respect. Prejudice and discrimination in any form on the basis of race, sex, age, religion, national origin, gender identity/expression, sexual orientation, disability status, socio-economic status, or other forms of identity are strictly prohibited. All students are entitled to the proper usage of names and pronouns that they designate.
Religious Observance
As a nonsectarian, inclusive institution, NYU policy permits members of any religious group to absent themselves from classes without penalty when required for compliance with their religious obligations. The policy and principles to be followed by students and faculty may be found in the University Calendar Policy on Religious Holidays.
Disability Disclosure Statement
Academic accommodations are available to any student with a chronic, psychological, visual, mobility, learning disability, or who is deaf or hard of hearing. To obtain an accommodation, please contact the Moses Center for Student Accessibility.
mosescsd [AT] nyu [DOT] edu
Phone
1-212-998-4980
Address
Auditing
Auditors are subject to the following policies, as well as to applicable policies set by their school and/or degree program.
Who Can Audit
Pursuant to GSAS policy, only enrolled NYU students may audit the course.
Official vs. Unofficial Auditors
GSAS auditors may audit the course officially or unofficially. Official auditors must pay full tuition for the course, and they will receive 0 points of credit and a grade of R on their transcripts. Unofficial auditors do not pay tuition for the course, but they will have no record of their participation in the course. Please consult the GSAS Policies and Procedures Manual for more information.
Participation
Auditors may attend lectures and labs in-person and/or on Zoom. However, pursuant to NYU policy, seats in the classroom are reserved for enrolled students when the room is full. Auditors may have access to Brightspace, Campuswire, Gradescope, and the course GitHub Organization. Auditors may participate fully on Campuswire. Auditors may attend office hours, but the questions of enrolled students take priority.
Submission of Coursework
Auditors may submit homework assignments (including extra credit assignments) and reading quizzes to Gradescope, but they will not receive any feedback from the graders. Auditors will receive grades for reading quizzes, as well as unit test results for coding questions on homework assignments.
Final Project
Auditors may complete a final project if they wish, but they may not join a project group that includes at least one enrolled student. Auditors that choose to complete a final project will not submit a mini-proposal, full proposal, paper draft, or a final paper. However, they will have the opportunity to give an oral presentation about their project during Examination Week.