CS91.3 Lab 1: Review a Poster

Due Tuesday, January 25, by midnight (23:59, EST)

Goals

The goals for this lab assignment are:

  • Learn how to write a review for a research paper or poster

  • Practice how to review a research poster

  • Get comfortable with using reviewer guide from CS conferences

  • Get comfortable with two-page posters

  • (Back to Course Index Page)

1. Reviewer Guide

For this week, please read the below two sections of the Reviewer Guide:

  • Review content

  • Examples of Review Content

2. Review Examples

Please review the three examples below:

8-8-10, Best paper award Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research By Bernard Koch, Emily Denton, Alex Hanna, and Jacob Gates Foster.

8-9-9, Best paper award ATOM3D: Tasks on Molecules in Three Dimensions By Raphael John Lamarre Townshend, Martin Vögele, Patricia Adriana Suriana, Alexander Derry, Alexander Powers, Yianni Laloudakis, Sidhika Balachandar, Bowen Jing, Brandon M. Anderson, Stephan Eismann, Risi Kondor, Russ Altman, and Ron O. Dror.

7-7-10, ML and BCI EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction By Ard Kastrati and Martyna Beata Plomecka and Damian Pascual and Lukas Wolf and Victor Gillioz and Roger Wattenhofer and Nicolas Langer.

3. Write Your Own Review

  • Review this poster, KnowBias (two-page)

  • Write your own review based on the Reviewer Guide and Review Examples above. You should include:

    1. Summary and contributions: #At least five sentences, including its innovation, connection, and impact

    2. Strengths: #At least five sentences, with details from the poster to support your opinion

    3. Weaknesses: #At least five sentences, with details from the poster to support your opinion

    4. Correctness: #At least one sentence

    5. Clarity: #At least two sentences, example preferred but not required

    6. Relation to prior work: #At least recommend one addition citation to the author

    7. Reproducibility: #At least two sentences, example preferred but not required

    8. Additional feedback: #Optional

    9. Overall score: #At least one sentence

    10. Confidence score: #At least one sentence

    11. Broader impact: #At least two sentences, example preferred but not required

    12. Ethical concerns: #At least one sentence

  • The '#' parts above are the comments for each section, similar to comments in Python.

  • Email 'xqu1@swarthmore.edu' your Lab 1 write-up as a PDF file.

4. Notes

  • This lab is an individual assignment.

  • We plan to form teams (Student Pairs) starting next week.

  • The mid-term project, a two-page research poster, is an individual project.

  • The final project, a ten-page research paper, is a team project.

  • Most of the rest of the lab assignments of this course, are team assignments.

  • Lab assignments will typically be released on Wednesday and will be due by midnight on the following Tuesday. This lab was released on 01/19 and will be due by midnight on 01/25.