•1 min read•from Machine Learning
[D] ICML reviewer making up false claim in acknowledgement, what to do?
Our take
When facing a situation where an ICML reviewer has made inaccurate claims about your method's performance, it's crucial to address the issue thoughtfully. Begin by clearly documenting your hyperparameter comparisons to substantiate your rebuttal. In your response, emphasize the discrepancies between the reviewer's assertions and the evidence presented in your paper. Maintain a professional tone and focus on constructive dialogue. This approach not only clarifies misunderstandings but also reinforces the credibility of your work, inviting a fair reassessment of your research.
In a rebuttal acknowledgement we received, the reviewer made up a claim that our method performs worse than baselines with some hyperparameter settings. We did do a comprehensive list of hyperparameter comparisons and the reviewer's claim is not supported by what's presented in the paper.
In this case what can we do?
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