Towards impactful challenges: post-challenge paper, benchmarks and other dissemination actions
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Acceso en línea: | |
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| _version_ | 1866913699969630208 |
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| author | Marot, Antoine Rousseau, David Zhen Xu |
| author_facet | Marot, Antoine Rousseau, David Zhen Xu |
| contents | The conclusion of an AI challenge is not the end of its lifecycle; ensuring a long-lasting impact requires meticulous post-challenge activities. The long-lasting impact also needs to be organised. This chapter covers the various activities after the challenge is formally finished. This work identifies target audiences for post-challenge initiatives and outlines methods for collecting and organizing challenge outputs. The multiple outputs of the challenge are listed, along with the means to collect them. The central part of the chapter is a template for a typical post-challenge paper, including possible graphs and advice on how to turn the challenge into a long-lasting benchmark. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_06036 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Towards impactful challenges: post-challenge paper, benchmarks and other dissemination actions Marot, Antoine Rousseau, David Zhen Xu Machine Learning Artificial Intelligence The conclusion of an AI challenge is not the end of its lifecycle; ensuring a long-lasting impact requires meticulous post-challenge activities. The long-lasting impact also needs to be organised. This chapter covers the various activities after the challenge is formally finished. This work identifies target audiences for post-challenge initiatives and outlines methods for collecting and organizing challenge outputs. The multiple outputs of the challenge are listed, along with the means to collect them. The central part of the chapter is a template for a typical post-challenge paper, including possible graphs and advice on how to turn the challenge into a long-lasting benchmark. |
| title | Towards impactful challenges: post-challenge paper, benchmarks and other dissemination actions |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2312.06036 |