Recent successes in the Machine Learning community have led to a steep increase in the number of papers submitted to conferences. This increase made more prominent some of the issues that affect the current review process used by these conferences. The review process has several issues that may undermine the nature of scientific research, which is of being fully objective, apolitical, unbiased and free of misconduct (such as plagiarism, cheating, improper influence, and other improprieties). In this work, we study the problem of reviewers' recruitment, infringements of the double-blind process, fraudulent behaviors, biases in numerical ratings, and the appendix phenomenon (i.e., the fact that it is becoming more common to publish results in the appendix section of a paper). For each of these problems, we provide a short description and possible solutions. The goal of this work is to raise awareness in the Machine Learning community regarding these issues.
翻译：最近机器学习界的成功导致向会议提交的文件数量急剧增加,使影响这些会议目前使用的审查进程的一些问题更加突出,审查过程有若干问题可能损害科学研究的性质,科学研究是完全客观、非政治、公正和没有不当行为的(例如,图谋、欺骗、不当影响和其他不当行为)。在这项工作中,我们研究了审查员的招聘问题、违反双盲程序、欺诈行为、数字评级偏见和附录现象(例如,在一份文件的附录部分公布结果已变得日益普遍),我们对每一个问题都作了简短的描述和可能的解决办法。这项工作的目的是提高机器学习界对这些问题的认识。
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