True. Who am I to say what is good and what's not, but I tend to enjoy simple papers with good ideas much more than papers that contain many moving parts (I am 100% unable to get that kind of result but I can enjoy it :) ).

I kind of treat complicated papers without robust code as noise or maybe a source of ideas, but when I try to implement it it's mostly not working as well as expected - e.g., I had to implement a model for a task related to speech and I have no expertise in the field, most of the models I tried to use were really bad in comparison to a good, simple solution (inspired by ResNet), and I found a model that performs better only due to preprocessing. It's hard to come up with new ideas so I am happy there is so much information, but sometimes it's too much.