Generative AI, and in particular Large Language Models (LLMs) such as GPT-4, has already changed how we work and study. But this is just the beginning, as it has the potential of assisting and perhaps eventually automating knowledge workers in all areas, from law, medicine, to teaching and mental health therapists. This course will focus on the general principles and the latest research on methodologies and tools that can be applied to all domains. This is a project-oriented course, where students will gain hands-on experience in either methodology research or applying the concepts to create useful assistants for a domain of their choice.
Topics include:
Homeworks:
There will be two homeworks at the beginning of the quarter, where students will create hallucination-free LLM-based agents using given tools. Students can build upon this work for their project in the rest of the quarter. Homework will be done in groups of 2.
| 👩🏫 Instructor | Monica Lam ( lam at cs)
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| 🧑🏫 Head TA | Harshit Joshi ( harshitj at cs)
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| 👩🏫 TA | Pauline Arnoud ( parnoud) |
| 👩🏫 TA | Emily Bunnapradist ( embunna) |
| 🧑🏫 TA | Adam Chun ( adamchun) |
| 🧑🏫 TA | Steven Feng ( syfeng) |
| 👩🏫 TA | Seonghee Lee ( shl1027) |
| 🧑🏫 TA | Shiyu Zhao ( shiyuz) |
| 🕒 Time | Mon, Wed 3:00-4:20pm |
| 🏫 Location | Gates Room B1 |
| 💳 Credits | 3-4 units |
| Harshit Joshi | Wednesday 1:30 pm - 2:30 pm, Gates 323, Zoom meeting link |
Lectures: Monday/Wednesday 3:00-4:20pm in person in Gates B1. Attendance is mandatory.
Recordings: video recordings of the lecture can be found on Canvas.
Slides: can be found on the Schedule and in the lecture slides folder on Canvas. Posted lecture slides are missing important details to facilitate student participation. Please make sure you watch the lectures.
Homework: can be found on the Schedule and submissions will be on Gradescope.
Contact: Students should ask all course-related questions on Ed, where you will also find announcements. For external inquiries, personal matters, or in emergencies, you can send an email to our staff email cs224v-aut2425-staff@lists.stanford.edu
Academic accommodations: If you need an academic accommodation based on a disability, you should initiate the request with the Office of Accessible Education (OAE). The OAE will evaluate the request, recommend accommodations, and prepare a letter for the teaching staff. Once you receive the letter, send it to the course staff email at cs224v-aut2425-staff@lists.stanford.edu. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations.
Audit Requests: To audit the course, please send an email to course staff email at cs224v-aut2425-staff@lists.stanford.edu, with the subject line "audit cs224v request."
Course Participation: We offer the course on SCPD to serve remote students; it is not to allow students take conflicting courses. In-class attendance and participation are an important part of the course. We allocate 15% of the course grade to class participation, which is important to make the most out of the course.
Prerequisites: one of LINGUIST 180/280, CS 124, CS 224N, CS 224S, 224U.
Update (9/20): CS224V has limited enrollment so as to provide adequate project/research supervision to students. At this point, we have given out the remaining spots to a few more students who need to take this course or have demonstrated that they need little project supervision. We anticipate that only a few spots may open up due to attrition; if you have not heard from us, it is unlikely that we can accommodate you. We apologize that we cannot accommodate all the students wishing to take the course this year.
Grading is according to the following scheme: