Course Information

• Course: LIN 389C, Research in Computational Linguistics, 39815
• Semester: Spring 2020
• Webpage: http://jessyli.com/courses/lin389c
• Meeting: T 10:00 - 1:00, Compling Lab (RLP 4.422) (Mar 30 onwards: head to Canvas to join via Zoom)

Contact information

• Course organizer: Jessy Li; email: jessy@austin.utexas.edu
  • Office hours: TTH 3:30PM-5:00PM, RLP 4.728 (Mar 30 onwards: head to Canvas to join via Zoom)

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. Typically one of the students in the class will be responsible for giving a short initial summary of the paper and for preparing some questions to get the discussion going.
• 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

This is the list of suggested topics we will discuss this semester (to be refined):

• Factuality in natural language generation, e.g., summarization
• Question answering: multi-hop, open domain, and reasoning
• Natural language inference, annotation artifacts, and downstream applications
• Coreference: datasets, ambiguity, applications
• Theories in dialogue
• Generating poems and lyrics
• Low resource MT & IE
• Multi-lingual semantic parsing
• Common sense, semantic plausibility
• Distributional models and psycholinguistics
• Discourse and argumentation

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, 1/21
  • 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, 1/28
  • We will read Kryscinski et al., Neural Text Summarization: A Critical Evaluation. Laura will lead the discussion.
• Week 3, 2/4
  • We will read Kryscinski et al., Evaluating the Factual Consistency of Abstractive Text Summarization. Shrey will lead the discussion.
• Week 4, 2/11
  • We will read (1) Throne et al., FEVER: a large-scale dataset for Fact Extraction and VERification; (2) Schuster et al., Towards Debiasing Fact Verification Models. Prakhar will lead the discussion.
• Week 5, 2/18
  • We will read Massarelli et al., How Decoding Strategies Affect the Verifiability of Generated Text. Eric will lead the discusssion.
  • Kyle Mahowald will visit the class.
• Week 6, 2/25
  • We will read Richardson et al., Probing Natural Language Inference Models through Semantic Fragments. Yejin will lead the discussion.
  • Eunsol Choi will visit the class. Find out more about TyDi QA here.
• Week 7, 3/3
  • We will read Pavlick and Kwiatkowski, Inherent Disagreements in Human Textual Inferences. Elisa will lead the discussion.
  • Martha Palmer will visit the class.
• Week 8, 3/10
  • We will read He et al., Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. Pengxiang will lead the discussion.
• Midterm papers due midnight Sunday Mar 15
• Week 9, 3/17 (Spring break)
• Week 10, 3/24 (Extended spring break due to COVID-19)
• Week 11, 3/31
  • We will read Hu et al., Learning to Reason: End-to-End Module Networks for Visual Question Answering. Ching-Da will lead the discussion.
• Week 12, 4/7
  • We will read Gupta and Lewis, Neural Compositional Denotational Semantics for Question Answering. Gabriella will lead the discussion.
• Week 13, 4/14
  • We will read Gupta et al., Neural Module Networks for Reasoning Over Text. Alex will lead the discussion.
• Week 14, 4/21
  • We will read Sakaguchi et al., WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale. Neha will lead the discussion.
• Week 15, 4/28
  • We will read Dobnik et al., Modelling language, action, and perception in Type Theory with Records. Prateek will lead the discussion.
• Week 16, 5/5
  • We will read Purver et al., Incremental Semantic Construction in a Dialogue System. Sriram will lead the discussion.
  • Plans for next semester
• Final papers due: 11:59pm, 5/15