Reaction Comments

To help presenters direct class discussions better, everyone is expected to write a set of short reactions for each assigned paper (in the form of NB annotations). Your reactions should not summarize the paper. Instead, they should focus on your critique of the paper. You may find this guideline for reading a research paper helpful (thanks to Prof. Hwa for this pointer).

Mandatory requirements:

  1. Always include one annotation that explains whether and how you think the paper is interesting from an NLP perspective. What are the opportunities and challenges in applying NLP to this problem? If not published in an NLP venue, how would this work need to be changed to contribute to the NLP community?
  2. Also contribute (at least) one additional substantive annotation per paper. Your annotations may have a number of forms: (a) You may compare the work to related material; (b) You may hypothesize about ways in which the work could have been improved; (c) You may think about ways to expand on the work (conceptually or computationally); (d) You may critique the work, including its conceptual framework, methodology, and/or results.
Other options:

Additional substantive annotations and/or responses to other posts, as well as descriptions of things you don't understand that you would like the class to discuss, are encouraged.

Grading:

Reaction annotations are due by 11:30 AM the day before the class during which the paper will be presented (that is, 24 hours in advance).

For cach class, you will receive a commentary score of 1 (satisfactory) or 0 (unsatisfactory). Late assignments receive 0.