Most papers are wrong. Not necessarily wrong in an essential way, but most of them overstate their claims. There's a rule of thumb in the machine learning comm

Most papers are wrong. Not necessarily wrong in an essential way, but most of them overstate their claims. There's a rule of thumb in the machine learning community: if you want an algorithm that does X well, find a paper on doing X, and implement the method that the paper compares its proposal against. That way you're near state of the art, but you're also using a method that many people have used and tested.