Course Information

• Course: LIN 389C, Research in Computational Linguistics, 40070
• Semester: Fall 2023
• Webpage: http://jessyli.com/courses/lin389c
• Canvas: https://utexas.instructure.com/courses/1373203
• Meeting: W 12-3, RLP 4.422

Contact information

• Course organizer: Jessy Li; email: jessy@austin.utexas.edu
  • Office hours: T/TH 10-11; Location: RLP 4.728

Course Purpose

To teach about, encourage, and give students time for research. Also to establish vertical cohorts among students interested in the same subfield.

Course Organization

There are six constituencies who will not be treated exactly equally in the course because their needs are different:

• first-year students: need general context and help on first research projects and first-year papers;
• second-year students: need feedback on the research they have done, prepare for further research, and write second-year papers;
• third-year students: need to write their Qualifying Papers (QP), write grant proposals;
• post-candidacy pre-proposal students: need to write and present their dissertation proposals;
• post-candidacy dissertation students: need to write dissertations, get feedback;
• students from other departments: needs will vary. NOTE that this course is designed to provide support and necessary foundations to research in Computational Linguistics, rather than an overview of research topics. You are expected to carry out one research project throughout the semester.

Course Components

• Suggested topic list
• Research seminar: This semester we focus on a recent papers in computational linguistics. Topics and readings will be given under schedule. For each paper, each student will prepare 3 bullets about what you like or dislike about the paper, plus questions.
• Discussion of ongoing student research:
  • Round-table: short presentations by all participants about their current research. This will happen almost every week.
  • On-going research: longer presentations (30 minutes or an hour including discussion), students, faculty, auditors if they wish.
  • Dissertation proposal presentations.
  • Dissertation progress talks.
  • Practice talks for conference presentations.

Requirements

• First-year students: Attend all classes/activities. Talk about research.
  First semester, submit literature discussion sketch halfway through the semester, submit literature discussion at end of semester.
  Second semester, submit first-year paper draft halfway through the semester, submit first-year paper at end of semester.
• Second-year students: Attend all classes/activities. Talk about research.
  First semester, submit research discussion draft halfway through the semester, submit research discussion paper at end of semester.
  Second semester, submit second-year paper draft halfway through the semester, submit second-year paper at end of semester.
• Third-year students: Attend all classes/activities. Talk about research.
  First semester, submit QP proposal halfway through the semester, submit QP progress report at end of semester.
  Second semester, submit QP draft halfway through the semester, submit QP at end of semester.
• Post-candidacy, pre-proposal students: Attend all presentations. Talk about research.
• Dissertation-writing students: Attend all presentations, give at least one presentation during semester on doctoral research.
• Students from other departments: a course project, with 2 documents: intermediate report (2-3 pages), final report (8 pages).

Topics

See Google Doc (link on Canvas)

Schedule

Each week, unless noted otherwise, we use the first part of the class to discuss the topic of the week, and we use the second part for a round-table discussing people’s research.

• Week 1, 8/23
  • Plan for the semester: Which topics to focus on, who gives talks where.
  • Extended round table: Research results and research/publication plans for the spring.
• Week 2, 8/30
  • Hase et al., Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs
• Week 3, 9/6
  • Workshop on git/cluster workflows led by Venkat and Gabriella
• Week 4, 9/13
  • Shankar will present two of his papers:
    • Can LMs Learn New Entities from Descriptions? Challenges in Propagating Injected Knowledge
    • Propagating Knowledge Updates to LMs Through Distillation
• Week 5, 9/20
  • Cohen et al., Evaluating the Ripple Effects of Knowledge Editing in Language Models
• Week 6, 9/27
  • Jung et al., Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations
    • Jaehun Jung will join the discussion
  • Workshop on the academic job market
    • Tanya Goyal will join the discussion
• Week 7, 10/4
  • Tom McCoy will present his work, Modeling rapid language learning by distilling Bayesian priors into artificial neural networks
• Week 8, 10/11
  • Zheng et al., Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
• Week 9, 10/18
  • Lio Wong will present From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought
  • Midterm papers due
• Week 10, 10/25
  • Zeng et al., Evaluating Large Language Models at Evaluating Instruction Following
• Week 11, 11/1
  • Geiger et al., Causal Abstraction for Faithful Model Interpretation
• Week 12, 11/8
  • Nathan Schneider visit; reading on Canvas
• Week 13, 11/15
  • Michael Hannah will present his paper: How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model
• Week 14, 11/22 (Thanksgiving Break)
• Week 15, 11/29
  • Extended roundtable/EMNLP practice talks, and plans for next semester.
• Final paper deadline: Dec 6, noon; hard deadline: Dec 9, midnight