Text Analytics: Machine Learning for Text

Text Analytics: Commonsense Reasoning for Language Understanding

Course Description

Text Analytics: Commonsense Reasoning for Language Understanding

Commonsense knowledge, like knowing that “not everything that looks like fruits is edible” or “rain makes things wet“, is essential for humans to live and communicate. To better understand humans and take more reasonable actions, learning and incorporating commonsense is essential for AI. The seminar will cover the latest research on commonsense modeling for natural language processing. We will talk about casting common sense tasks as NLP problems; review existing methods and benchmarks; assess our current knowledge about commonsense capabilities of language models, and investigate ways to incorporate commonsense into downstream tasks.

Organisation

All information will be distributed via the Moodle eLearning platform.

Teaching Staff

  • Nafise Sadat Moovasi
  • Prof. Dr. Iryna Gurevych

Literature

Will be announced during the seminar.

Timetable

The first sessions will consist of introductory lectures to cover the basics of machine learning methods used for NLP tasks. The program for the remainder of the seminar will be determined according to the number of participants.

FAQ

When you should send me a request for the office hour: 2 weeks before your presentation (if you are the first week presenter, you can send it 1 week before)

What you should tell me in your e-mail: (1) Preferred half an hour time-slot if you have any preference; (2) Your name and your paper;

When you should send me your presentation draft: As early as possible, not later than 3 days before our meeting