Foundations of Artificial Intelligence (FAI) Group
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Seminar: Search Problems in Natural Language Processing

Basics. Seminar, 7 graded ECTS points.

The seminar will be run in a block format. There will be an initial meeting on Thursday, April 20, 17:00--18:00. All student presentations will be given on a single day after the end of term. A detailed schedule is given below.

All meetings will take place in room 3.06, Building E1 1. The seminar language is English throughout.

Your task will be to read and understand a piece of research, to write a summary paper in your own words, to give a presentation, and to provide detailed feedback for the paper and presentation of a fellow student.

All email interaction must be pre-fixed with "[NLP17]" in the email subject.

No plagiarism. It is Ok (and encouraged!) to use web resources to further your understanding of your assigned topic. However, it is inadmissible to use pieces of such material for your summary paper or presentation. Any plagiarism will result in disqualification from the seminar.

Content. Search problems, involving the exploration of a large combinatorial space of possible options, occur in several sub-areas of Natural Language Processing (NLP), including sentence generation, parsing, text-to-speech synthesis, and the quantification of linguistic distance. These search problems relate intimately to search problems considered in Artificial Intelligence and, in particular, in Automatic Planning. The seminar considers sentence generation, as search in a space of partial sentences, and parsing, as search in a space of matching grammatical expressions, where that connection is particularly direct as the search space is generated by a set of formal rules -- the grammar -- akin to the action descriptions generating transitions in planning. Connections between NLP and Automatic Planning have been made (and we consider some of these in the seminar), but the fields have largely developed independently and the working hypothesis of the FAI group is that many more opportunities for technology transfer exist.

Prerequisites. Participants must have successfully completed an introductory course in Artificial Intelligence. They should be familiar with automatic planning at least to the extent of the material covered in the Artificial Intelligence course. Successful participation in our Automatic Planning course will be an advantage, but is not absolutely necessary to follow the seminar.

Registration. The seminar has participation slots for 9 students. Registration for the seminar will be open from April 1 until April 24 (midnight). Please do not try to register ahead of time; we will only consider applications reaching us within the given time window!

To apply for registration, send an email to Álvaro Torralba. In the email, give a brief description of your relevant background. In particular, say whether you got a BSc and from which university, and describe previous lectures/seminars you completed in the areas of Artificial Intelligence, Automatic Planning, and Natural Language Processing. For each relevant course, state the grade you obtained in that course. Say a few words regarding why you are interested in participating in the seminar.

You will be notified by email on April 24, informing you whether or not you are registered.

Attention! As there always are more students than we have places, to be fair towards your fellow students please do only sign up if you're really interested in following the seminar through to the end. In particular, according to the new study regulations, you are only allowed to withdraw within three weeks after the briefing of the seminar, i.e., until May 7. Later withdrawal counts as "failed".

Grading. The final grading will be based on:

Summary Paper. For the summary paper, you must use this tex template. Note in particular that you are required to read at least 2 related papers, for the related work section.The seminar paper should be about 4 pages long (not counting the literature list, and in the double-column format of the template). This is a rough guideline, not a strict rule. If you need, say, 5-6 pages to do your paper justice then definitely do so.

Schedule and Deadlines.

NOTE: If you have a problem with the date of the block seminar (presentation day), e.g. a close-by exam, please let us know AS SOON AS POSSIBLE. We will try to re-schedule.

Topics. Each participant will be assigned one topic. The overall amount and difficulty of the material associated with each topic is roughly balanced.

Area 1: TAG Sentence Generation.

  1. Sentence generation as a planning problem. Mentors topic 2, is mentored by topic 3.
  2. Results of planning for sentence generation. Mentors topic 3, is mentored by topic 1.
  3. Planning for Giving Instructions. Mentors topic 1, is mentored by topic 2.

Area 2: CCG Chart Realization.

  1. CCG Chart Realization. Mentors topic 2, is mentored by topic 3.
  2. Efficient Realization in CCG. Mentors topic 3, is mentored by topic 1.
  3. Dead-end pruning for realization in CCG. Mentors topic 1, is mentored by topic 2.

Area 3: Search in CCG Parsing.

  1. A* CCG Parsing. Mentors topic 2, is mentored by topic 3.
  2. A* CCG Parsing with Supertagging. Mentors topic 3, is mentored by topic 1.
  3. LSTM CCG Parsing. Mentors topic 1, is mentored by topic 2.