Boxplots or violinplots? This is quite a general question, perhaps somewhat opinion-based. 

In most papers people use boxplots to visualize a certain distribution, yet violinplots are able to give more information. Violinplots are made by performing a kernel density estimation on your distribution. 

Are there objective arguments to use one over the other? Or maybe there are specific situations in which one would prefer one over the other? 

An example of both can be found here:
Hugely dependent on both user and audience preference (violin plots being more unusual could throw people), so it is mostly up to you.

One main reason to go for a violin plot is to give more detail about the distribution, as box plots just give hard stops at the mean, stddev and 2 stddevs. Therefore if you think there is interesting information contained in the distribution between those points go violin.

The other main reason is they're more eye catching on Kaggle ;)