COMP 790.139: Natural Language Processing (Fall 2017)

Instructor: Mohit Bansal
Units: 3
Office: SN 258
Lectures: Wed 10:10am-12:40pm, Rm FB-008
Office Hours: Wed 12:40pm-1:40pm (by appointment) (SN 258)
Course Webpage:
Course Email: nlpcomp790unc -at-

TA: Yixin Nie
TA’s Email: yixin1 -at-
Office: SN 372
Office Hours: Wed 2:30pm-3:30pm (SN208 -- 2nd floor reading room)



This course will be based on the artificial intelligence and machine learning field of natural language processing (NLP, or computational linguistics), and its important multimodal connections to computer vision and robotics. First we will cover traditional topics of NLP such as tagging, parsing, coreference resolution, sentiment analysis, summarization, question-answering, and translation. Then, we will cover more recent topics of multimodal, grounded, and embodied semantics (i.e., language with vision and speech, for robotics), language generation and dialogue, and interpretable deep learning.

Topics (tentative, based on time)


Since this is a graduate research-level class, some machine learning and coding experience is expected (see references below). Previous courses in probability and linear algebra are also highly recommended.

Grading (tentative)

Grading will consist of:

Details in first class intro lecture slides. There will not be any exams. All submissions should be emailed to:

Lateness Policy

Students are allowed 3 free late days for assignments over the semester. After that, late assignments will be accepted with a 10-20% reduction in value per day late.

Collaboration Policy

Homeworks and paper summaries have to be written and submitted individually. Projects are encouraged to be done in pairs (but individual projects are fine too, e.g., if it relates to your current research), with clearly outlined contributions from each team member.

Reference Books

Schedule (tentative)

DateTopic (& slides) Readings Discussion LeadersTodo's (Assignments, Homeworks)
Aug 23Intro to the Course, Language Modeling (N-gram, RNNs, etc.) (slides) SLP3 Chapters 1-4, 8; SLP2 Chapters 1-4 Mohit Summary due Sep05 midnight for SLP3 Sections 4.5, 8.4, 8.5
Aug 30Travel (make-up sessions emailed to you) -- -- -
Sep 06 Word/Sentence Embeddings, Text Classification (slides) SLP3 Chapters 6, 15, 16 Mohit -
Sep 13 Part-of-Speech Tagging, NER, Sequence Labeling, Coreference Resolution (slides) SLP3 Chapters 9, 10, 24; SLP2 Chapters 5, 6, 21 Mohit Summary due Sep24 midnight for SLP3 Sections 9.5, 10.5
Sep 20 Syntactic Parsing (slides) SLP3 Chapters 11, 12, 13, 14; SLP2 Chapters 12, 13, 14 Mohit Coding HW1 (Word Embedding Training, Visualization, Evaluation) -- due Oct5
Sep 27 SRL, Semantic Parsing, Compositional Semantics 1 (slides) SLP3 Chapters 22; SLP2 Chapters 18, 19, 20 Mohit -
Oct 04 Claire Cardie (Cornell) Talk, Project Brainstorming -- Mohit -
Oct 11 Semantic Parsing 2, Question Answering (slides) SLP3 Chapters 28; SLP2 Chapters 23 Mohit -
Oct 18 Midterm Project Presentations -- All Students -
Oct 25 Document Summarization, Machine Translation (slides) SLP3 Chapters 26, 27; SLP2 Chapters 23, 25 Mohit Midterm Write-ups Due Oct30 midnight
Nov 01 Machine Translation 2 (slides);
Animesh Garg (Stanford) Talk
SLP3 Chapters 26; SLP2 Chapters 25 Mohit Coding HW2 (Sequence-to-Label Learning for Entailment Recognition) -- due Nov17
Nov 08 Machine Translation 3 (Neural), Dialogue Models (slides) SLP3 Chapters 29, 30; SLP2 Chapters 24 Mohit -
Nov 15 Language+Vision (slides);
Guest Lectures by Ramakanth, Hao
-- Mohit -
Nov 22 Thanksgiving Recess (no class) -- Mohit -
Nov 29 Language+Robotics (slides) -- Mohit -
Dec 06 Final Project Presentations -- All Students -
Dec 12 Project Write-ups Due -- All Students Project Write-ups Due


The professor reserves the right to make changes to the syllabus, including project due dates. These changes will be announced as early as possible.