How to Read a Paper (2016) [pdf]
I know there are a lot of ML researchers and practitioners here - and I have unfortunately only a very shallow experience with reading ML papers, more so with the recent output.<p>But, I have to ask, how do you get a feel that the content actually looks correct, and not just only quack? The improvements are usually in the 1% range, from old models to new models, and the models are complex. More often than not also lacking code, implementation / experiment procedures, etc.<p>Basically, I have no idea if the paper is reproducible, if the results are cherry picked from hundreds / thousands of runs, if the paper is just cleverly disguised BS with pumped up numbers to get grants, and so on.<p>As it is right now, I can only rely on expert assurance from those that peer review these papers - but even then, in the back of my mind, I'm wondering if they've had time to rigorously review a paper. The output of ML / AI papers these days is staggering, and the systems are so complex that I'd be impressed if some single post. doc or researcher would have time to reproduce results.