1.0 KiB
First Pass
Category: This is a review paper.
Context: This paper tries to keep up with where formal methods are for machine learning based systems. It is not necessarily a controls paper, but a broader machine learning paper in general.
Correctness: Really well written on the first pass. Easy to understand and things seem well cited.
Contributions: Great citations showing links to different papers and also provides nice spots for forward research. Talks about how verification needs to be done along the whole pipeline: from data prep to training to implementation. There needs to be more work on proving things about model behavior, but in general this review has a positive outlook on the field.
Clarity: Very well written, easy to understand. Except, what is abstractification of a network?
Second Pass
What is the main thrust?
What is the supporting evidence?
What are the key findings? Local robustness
Third Pass
Recreation Notes:
Hidden Findings:
Weak Points? Strong Points?