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Seminar on Large Language Models (COMP790-101 at UNC Chapel Hill, Fall 2022)
| Date | Stars |
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| 2026-07-31 | 313 |
| 2026-08-06 | 313 |
| 2026-09-20 | 313 |
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# COMP790-101: Large Language Models Instructor: [Colin Raffel](http://colinraffel.com) Meeting time: Mondays and Wednesdays, 1:25-2:40pm Classroom: SN 011 Office hours: By appointment Language models, which are trained to predict text given other text, underly many recent successes in natural language processing and artificial intelligence. Whether used for transfer learning (using language modeling as a pre-training objective before subsequent fine-tuning on a downstream task) or prompting (formulating an input sequence that induces a model to perform a desired task without any training), language modeling has proven to be an effective way of imbuing models with useful capabailities. These capabilities have been observed to consistently improve as the size of the language model increases, which has led to a focus on developing ever-larger language models. In this course, we will survey the history of language model scaling, as well as recent advances in building, analyzing, and using large LMs. The course will use a [role-playing seminar format](https://colinraffel.com/blog/role-playing-seminar.html), described in more detail below. ## Prerequisites Students must have experience with machine learning (preferably deep learning) and the basics of modern natural language processing. Before taking the class, you should be able to read a recent machine learning or natural language processing conference paper and come away with a decent understanding of the basic concepts and ideas proposed in the paper (but not necessarily a deep, perfect understanding of every last detail). ## Course Structure This class will use a [role-playing seminar](https://colinraffel.com/blog/role-playing-seminar.html) format where students take on different roles and present papers to one another. All grading will be based on these presentations and course participation; there will be final project or other coursework. ### Readings Each class will involve the presentation and discussion of two papers. The pair of papers covered in each class session are meant to complement each other, e.g. because one paper might be the historical precedent of the other, or the papers were contempraneous, or they present different viewpoints on the same topic. Before each class, everyone is required to have read both papers. Students will be divided into four groups. Two groups will present on Mondays and the other two groups will present on Wednesdays. In a given class session, students in the presenting groups will each be given a rotating role (described below). This role defines the lens through which they read the paper and determines what they prepare for the in-class discussion. Students in the non-presenting groups are also required to read the papers, complete a quick exercise (described below), and come to class ready to discuss. All students will obtain a thorough understanding of the chosen papers and will develop their paper reading, literature review, and prototyping skills. #### Presentation roles This seminar is organized around the different "roles" students play each week: Reviewer, Archaeologist, Researcher, Hacker, Diagrammer, and (possibly) Blogger. - **Reviewer:** Complete a full critical, but not necessarily negative, review of the paper. Follow the [guidelines for NeurIPS reviewers](https://neurips.cc/Conferences/2022/ReviewerGuidelines) (under "Review Form"). Please complete the "Strengths and Weaknesses" and "Questions" sections and assign an overall score; you can skip the rest of the review (including writing a summary since all students should have read the paper). - **Archaeologist:** Determine where this paper sits in the context of previous and subsequent work. Find and report on one prior paper *that we are not reading in this class* that substantially influenced the current paper **or** one newer paper *that we are not reading in this class* that was heavily influenced by the current paper. - **Hacker:** Implement a s
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matched fp:c20035b41a744092, llm:Repository description: 'Seminar on Large Language Models (COMP790-101 at UNC Chapel Hill, Fall 2022)'. No code/topics provided; educational course materials on LLMs.