3 ms·

My experience has been that the older CS papers (from the 60s, 70s, 80s) commonly have very clear, readable text, not weighed down with unnecessary "academic st

My experience has been that the older CS papers (from the 60s, 70s, 80s) commonly have very clear, readable text, not weighed down with unnecessary "academic style" verbiage. It's the newer stuff that's painful to read. I don't know whether this is a general change in fashion, or because the early papers in a field are dealing with simpler ideas (at least ideas that are not reliant on a decade of prior papers and terminology), or because it's only the good old papers that still come up in literature reviews and all the badly written stuff has long since been forgotten.

fxtentacle 2y ago
The constant fighting between Schmidhuber and LeCunn should be well known in here. But in my opinion, both of them have been involved with fantastic papers that are both painless to read and full of useful info: CTC loss: https://www.cs.toronto.edu/~graves/icml_2006.pdf https://www.cs.toronto.edu/~graves/icml_2006.pdf DeepLearning: https://hal.science/hal-04206682/document https://hal.science/hal-04206682/document And both of these papers are new and on more recent research, so it's not just old papers that are good. It's just that there is a flood of bad new papers drowning out a constant signal with additional noise.
matthewdgreen 2y ago
As a researcher I can say the opposite. In my field (cryptography) modern papers usually start by specifying formally exactly what the algorithm APIs look like; then they provide precise security definitions; then they describe algorithms; then they provide formal (if detailed) proofs of security. It’s long and detailed, but you get all the pieces you need for precision and you know where to find it. Papers in the same conferences from 1982 are full of beautiful insights and they’re easy to read. But often that’s because they’re a five-page long story that might provide only a tiny subset of what we expect nowadays. They often don’t specify exactly what the algorithms do, they just kind of describe the ideas in English. Formal definitions are like three sentences of handwave. Proofs are similarly short or missing. Typically if you follow the citation chain you’ll find a dozen papers saying “we show that the original construction by Seminal Author is totally broken in this situation, but we show how to fix that with a small tweak and a better security definition.” Eventually you get to modern papers that actually start with the right definitions to deal with all that stuff, but take longer to read. Obviously to the layperson the short old papers are fun and full of insight! To an expert they’re still full of insight, but we wouldn’t let them out of our lab in that condition. It’s very much like comparing a beautiful old classic car to a modern car with safety features. They both look great: but you don’t want to get into even a minor fender bender in the old car.

fxtentacle 2y ago

The constant fighting between Schmidhuber and LeCunn should be well known in here. But in my opinion, both of them have been involved with fantastic papers that are both painless to read and full of useful info: CTC loss: https://www.cs.toronto.edu/~graves/icml_2006.pdf https://www.cs.toronto.edu/~graves/icml_2006.pdf DeepLearning: https://hal.science/hal-04206682/document https://hal.science/hal-04206682/document And both of these papers are new and on more recent research, so it's not just old papers that are good. It's just that there is a flood of bad new papers drowning out a constant signal with additional noise.

matthewdgreen 2y ago

As a researcher I can say the opposite. In my field (cryptography) modern papers usually start by specifying formally exactly what the algorithm APIs look like; then they provide precise security definitions; then they describe algorithms; then they provide formal (if detailed) proofs of security. It’s long and detailed, but you get all the pieces you need for precision and you know where to find it. Papers in the same conferences from 1982 are full of beautiful insights and they’re easy to read. But often that’s because they’re a five-page long story that might provide only a tiny subset of what we expect nowadays. They often don’t specify exactly what the algorithms do, they just kind of describe the ideas in English. Formal definitions are like three sentences of handwave. Proofs are similarly short or missing. Typically if you follow the citation chain you’ll find a dozen papers saying “we show that the original construction by Seminal Author is totally broken in this situation, but we show how to fix that with a small tweak and a better security definition.” Eventually you get to modern papers that actually start with the right definitions to deal with all that stuff, but take longer to read. Obviously to the layperson the short old papers are fun and full of insight! To an expert they’re still full of insight, but we wouldn’t let them out of our lab in that condition. It’s very much like comparing a beautiful old classic car to a modern car with safety features. They both look great: but you don’t want to get into even a minor fender bender in the old car.