User:Fgpacini/Choose an Article

Article Selection
Please list articles that you're considering for your Wikipedia assignment below. Begin to critique these articles and find relevant sources.

Article Title
Word embedding

Article Evaluation
Stub, low importance article. This article and embeddings in general are extremely important to modern deep learning methods, and the amount of contribution to this article doesn't seem to reflect that. There is no section describing use cases for word embeddings. The end of the limitations section describes BERT embeddings in a very brief and unclear way. Special focus is given to the applications of word embeddings to biological sequences, but no other applications or extensions are included.

Sources

https://snap.stanford.edu/node2vec/

https://github.com/google-research/simclr

https://openai.com/blog/clip/

https://arxiv.org/abs/2109.14084

Option 2

 * Article title
 * Music and artificial intelligence


 * Article Evaluation
 * No rating. This is the lowest quality article I found but also covers a somewhat niche topic, so may not be as important to contribute to. The article begins by listing several conferences which cover the topic without describing what it is. Some research applications are listed but it is very insufficient to explain the goals and tasks of the field. Common approaches in the past and present could be presented. The history section is very brief and doesn't cover any efforts within the last 25 years. The applications section describes several obscure projects without clearly explaining what they do or were designed for, while including many irrelevant details.

Sources

https://musicinformationretrieval.com/

Option 3

 * Article title
 * Self-supervised learning


 * Article Evaluation
 * Stub article. The intro section is poorly written and doesn't describe the concept in an intuitive way. The example section should also describe how each method uses SSL since that is the relevant portion to this article.

Sources

https://github.com/facebookresearch/simsiam

https://openai.com/blog/clip/