4 ms·

Fully agree. There's so many people who succumb to "not invented here" and then run blindly into solved issues. I keep repeating the story, but in 2020, I surp

Fully agree. There's so many people who succumb to "not invented here" and then run blindly into solved issues. I keep repeating the story, but in 2020, I surprisingly got #1 on the MPI Sintel benchmark for optical flow in the category "Clean EPE matched", by re-implementing a 15 year old paper. (And replacing their approximation of a quadratic solver with actually using a quadratic solver.) That said, I feel like it's not just machine learning which is flooded with useless preprints. It's the entire internet now. When I wanted to look up some context for quaternion math, it was surprisingly challenging to find something a bit more in-depth than motivated amateurs who try to sell their self-published ebook and/or Udemy course. No, "np.quaternion" is not a mathematical formula. In the end, it was easier to dig up my old paper book, which had a nice A4 overview page with all the relevant formulas.

hi-v-rocknroll 2y ago
The disconnect between laypeople and research is often compounded by the stilted language, undefined terminology and related knowledge assumptions, underspecified details, and incomplete presentation of code or examples for independent reproducibility. Research papers, to be maximally reusable and future-proof, should prefer to present information in as plain English as possible and commonly-used mathematic terminology and symbols rather than obscure forms where possible. Using big words (or Latin) doesn't add profoundness, but they can add artistic flair in other contexts where elucidation isn't the goal. ;-)
- Bluestein 2y ago
  Would using standard Basic English (https://en.wikipedia.org/wiki/Basic_English https://en.wikipedia.org/wiki/Basic_English) help?
- wheybags 2y ago
  And source code, for the love of god, give me source code so I don't have to guess what your underspecified description in the paper actually means.
- randomcarbloke 2y ago
  >in as plain English as possible This is exactly what they do, even domain specific language is selected to precisely convey meaning and differentiate from incorrect but close interpretations.
  - ungamedplayer 2y ago
    We must be reading very different papers.
- azornathogron 2y ago
  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.
- ragnese 2y ago
  > Research papers, to be maximally reusable and future-proof, should prefer to present information in as plain English as possible and commonly-used mathematic terminology and symbols rather than obscure forms where possible. Using big words (or Latin) doesn't add profoundness, but they can add artistic flair in other contexts where elucidation isn't the goal. ;-) As someone with a background in academia, I have to disagree with the assertion that papers should be written in "plain English" and some lowest-common-denominator of symbolism. It doesn't make me happy to argue against that, but the truth is that scientific papers MUST build on previous knowledge. No leading gene editing research paper is coming out with long-winded prose explaining what DNA and RNA are. No particle physics paper coming out of CERN is going to avoid quantum field theory jargon and terminology in the hopes that a lay person with a pre-calculus level of math education is going to be able to study the results and understand it. How many times longer would these papers be if they did try to do that? My calculus book from undergrad was some 600 pages long (it covered three semesters, to be fair)--now imagine that the people writing these papers read that 600 page book in their first one or two years of undergrad, and then proceeded to study their subject for AT LEAST another 6 years (closer to 8 for physics) before getting "Dr" in front of their name. How many pages would a research paper need to be for a lay person to understand? Probably pretty long. The truth is that there sometimes IS NOT a "plain English" way to explain something. Yes, you can use inaccurate metaphors and analogies about cats in boxes, but that doesn't lead to someone actually understanding the Schrodinger equation and Hilbert spaces. Believe it or not, scientists are not sitting around all day figuring out which Latin words will sound the most "profound" in their prose. Those are just the words they really actually use. Because words have meaning and some ideas are so common that they deserve to be condensed into a word, or an equation, or a symbol... At the end of the day, these papers are written to advance the respective field of study. The best way to do that is to write papers that are going to be relevant to people who might actually build on the results. The people who might actually build on the results are going to be people who understand the requisite background information. If Joe Schmoe wants to read a particle physics paper, then he better pull out his high school math books and work his way up to at least a masters degree level understanding of physics and mathematics. I would never go into the kitchen of a professional chef and tell her to stop referring to a "paring knife" or a "fillet knife" because I'm not familiar with cooking jargon. I wouldn't tell her that she has to re-explain what shape those knives have every time she explains a new recipe or technique. I would just have to learn the jargon if I actually cared enough.
glonq 2y ago
if it weren't for NIH, i'd bet that a majority of HN readers would be unemployed right now!

hi-v-rocknroll 2y ago

The disconnect between laypeople and research is often compounded by the stilted language, undefined terminology and related knowledge assumptions, underspecified details, and incomplete presentation of code or examples for independent reproducibility. Research papers, to be maximally reusable and future-proof, should prefer to present information in as plain English as possible and commonly-used mathematic terminology and symbols rather than obscure forms where possible. Using big words (or Latin) doesn't add profoundness, but they can add artistic flair in other contexts where elucidation isn't the goal. ;-)

Bluestein 2y ago
Would using standard Basic English (https://en.wikipedia.org/wiki/Basic_English https://en.wikipedia.org/wiki/Basic_English) help?
wheybags 2y ago
And source code, for the love of god, give me source code so I don't have to guess what your underspecified description in the paper actually means.
randomcarbloke 2y ago
>in as plain English as possible This is exactly what they do, even domain specific language is selected to precisely convey meaning and differentiate from incorrect but close interpretations.
- ungamedplayer 2y ago
  We must be reading very different papers.
azornathogron 2y ago
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.
ragnese 2y ago
> Research papers, to be maximally reusable and future-proof, should prefer to present information in as plain English as possible and commonly-used mathematic terminology and symbols rather than obscure forms where possible. Using big words (or Latin) doesn't add profoundness, but they can add artistic flair in other contexts where elucidation isn't the goal. ;-) As someone with a background in academia, I have to disagree with the assertion that papers should be written in "plain English" and some lowest-common-denominator of symbolism. It doesn't make me happy to argue against that, but the truth is that scientific papers MUST build on previous knowledge. No leading gene editing research paper is coming out with long-winded prose explaining what DNA and RNA are. No particle physics paper coming out of CERN is going to avoid quantum field theory jargon and terminology in the hopes that a lay person with a pre-calculus level of math education is going to be able to study the results and understand it. How many times longer would these papers be if they did try to do that? My calculus book from undergrad was some 600 pages long (it covered three semesters, to be fair)--now imagine that the people writing these papers read that 600 page book in their first one or two years of undergrad, and then proceeded to study their subject for AT LEAST another 6 years (closer to 8 for physics) before getting "Dr" in front of their name. How many pages would a research paper need to be for a lay person to understand? Probably pretty long. The truth is that there sometimes IS NOT a "plain English" way to explain something. Yes, you can use inaccurate metaphors and analogies about cats in boxes, but that doesn't lead to someone actually understanding the Schrodinger equation and Hilbert spaces. Believe it or not, scientists are not sitting around all day figuring out which Latin words will sound the most "profound" in their prose. Those are just the words they really actually use. Because words have meaning and some ideas are so common that they deserve to be condensed into a word, or an equation, or a symbol... At the end of the day, these papers are written to advance the respective field of study. The best way to do that is to write papers that are going to be relevant to people who might actually build on the results. The people who might actually build on the results are going to be people who understand the requisite background information. If Joe Schmoe wants to read a particle physics paper, then he better pull out his high school math books and work his way up to at least a masters degree level understanding of physics and mathematics. I would never go into the kitchen of a professional chef and tell her to stop referring to a "paring knife" or a "fillet knife" because I'm not familiar with cooking jargon. I wouldn't tell her that she has to re-explain what shape those knives have every time she explains a new recipe or technique. I would just have to learn the jargon if I actually cared enough.

glonq 2y ago

if it weren't for NIH, i'd bet that a majority of HN readers would be unemployed right now!