CS91.3 Lab 2: Review Papers

Due Tuesday, February 01, by midnight (23:59, EST)

Goals

The goals for this lab assignment are:

  • Learn how to conduct Literature Review

  • Practice how to review research papers

  • Get comfortable with using reviewer guide from CS conferences

  • Get comfortable with ten-page research papers

  • Learn how to find co-authors

  • (Back to Course Index Page)

1. Reviewer Guide

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

  • Review content

  • Examples of Review Content

2. Review Examples

Please read the three paper review 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. Find Your Co-author

Please use the Google Sheet here: Student Pairs in, Labs → Co-authors

4. Write Paper Reviews

  • Each team write FOUR reviews. The four papers are here: EEGEyeNet, Lotte_2018, Craik_2019,and Roy_2019.from Week 02.

  • Write your reviews 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 paper to support your opinion

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

    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 2 write-up as a PDF file.

5. Notes

  • Each team only needs to submit one PDF file, with both names on it.

  • The team members from the same team will get the same score.

  • Lab assignments will typically be released on Wednesday and will be due by midnight on the following Tuesday. This lab was released on 01/26 and will be due by midnight on 02/01.