OHAIHCJan 15, 2024

Challenge design roadmap

arXiv:2401.13693v1h-index: 8J. Data-centric Mach. Learn. Res.
Originality Synthesis-oriented
AI Analysis

This work addresses the need for structured planning in challenge design to improve quality and impact, but it is incremental as it synthesizes existing guidelines without introducing new methods.

The paper tackles the problem of designing effective challenges by providing guidelines for creating strong competition plans, drawing on preparation guidelines from organizations like Kaggle, ChaLearn, and Tailor, as well as the NeurIPS proposal template.

Challenges can be seen as a type of game that motivates participants to solve serious tasks. As a result, competition organizers must develop effective game rules. However, these rules have multiple objectives beyond making the game enjoyable for participants. These objectives may include solving real-world problems, advancing scientific or technical areas, making scientific discoveries, and educating the public. In many ways, creating a challenge is similar to launching a product. It requires the same level of excitement and rigorous testing, and the goal is to attract ''customers'' in the form of participants. The process begins with a solid plan, such as a competition proposal that will eventually be submitted to an international conference and subjected to peer review. Although peer review does not guarantee quality, it does force organizers to consider the impact of their challenge, identify potential oversights, and generally improve its quality. This chapter provides guidelines for creating a strong plan for a challenge. The material draws on the preparation guidelines from organizations such as Kaggle 1 , ChaLearn 2 and Tailor 3 , as well as the NeurIPS proposal template, which some of the authors contributed to.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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