Papers with Code + arXiv = Reproducible, Organized Research
Millions of scientific articles are shared openly via arXiv, a Cornell-powered website that focuses on open access to research. The Papers with Code website hosts academic papers which also share their backing software so that experiments can be faithfully reproduced. Through a joint collaboration, Papers with Code now provides category classification and code references for articles in the arXiv database.
We all love arXiv. Despite some quirks here and there, the premise is fantastic. The website provides an open-access archive to physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. As of October 2020, the site has over 1.7 million articles published. Anybody can access these articles at any time for no cost. This enables knowledge to be shared at a rate unheard of in previous generations, while still maintaining author attribution for credit assignment purposes.
Previously, new research developments mainly spread through the use of academic journals, which were human-prepared and likely not free. While this process achieves organization and sharing of information, it is biased and it is exclusive. The process is biased due to the collective biases of the workers that prepared the journals, accepting some and rejecting others. Of course, this likely works more often than it doesn't; however, I believe it's far from perfect. Additionally, the process is exclusive because it puts a price tag on obtaining the information. Yes, the world runs on exchanging items of value. That does not mean that value must be currency, nor does it mean that the currency must come directly from the end consumers.
The development of arXiv aids the movement towards freer information flow in the world. With this site, ground-breaking research can now disseminate through the world as fast as the internet's cables can pump it. Additionally, due to the open nature of the website, anyone can use the arXiv API to programmatically peruse the articles. Once you have an API, you. have a data set. Once you have a data set, you have the potential for beautiful visualizations, such as this one.
The fact that arXiv enables open research sharing alone is great for the global research community. However, the vast majority of new research in scientific fields now has software backing the research's findings. Failing to provide that software corresponds to a failing to provide all of the assets required to validate the research. In an information-centric world where most of the data available has been created in the past few years, the ability to use software to independently demonstrate that a research's findings are valid has become ever more important. Long gone are the days where you could read a paper and immediately know its validity. Randomized optimization algorithms and varying data sources require software and data to be provided in order to fully validate modern research.
Papers with Code (PwC), a website which organizes access to technical papers which also provide the software used to create the paper's findings, has grown immensely in the past few years. Coupled with the increase of publicly-available data sets, modern research has started to converge back towards full transparency and credibility. PwC has been consistently improving their website as well. One can easily navigate the state of the art via browsing either by task (e.g. object detection, sentiment analysis, etc) or by method (e.g. attention, convolutions). Additionally, as seen below, PwC also uses data collected from the papers to track how software frameworks and code availability are trending over time.
This service empowers the common user to enjoy the state of the art of machine learning like never before. Want to see some of the best models related to COVID-19? How about word embeddings, image generation, or speech recognition? Everything is right at your fingertips.
The greatest of results happen through collaboration, and these two websites are definitely no exception. PwC has teamed up with arXiv to hook directly into their website, providing readers links to software implementations for all papers that share them. There is no more need to click into the paper and search footnotes and references, hoping for the magical "GitHub" keyword to appear in all its majesty. Although a seemingly minor change, this integration increasingly encourages authors to provide these additional experiment details with submissions so that readers can better validate the findings. I imagine any model trained to predict the value of a paper would place high weight on the has_code feature!
The integration between PwC and arXiv also provides auto-categorization of papers, based on their titles and abstracts. Now, authors will have the option to adopt the auto-suggested category of their paper, in order to better organize content and increase reader reach. Continuing the spirit of open access, they have made the model repository publicly available right here. How great is that? A previous version of this model was not made available, which caused lots of confusion about its inner workings. That problem has now been resolved.
Due to the statistical nature of modern technology research, findings now require software and data experiment details in addition to white paper documentation for validation. The staggering rate of information production also needs open access and automated organization. The arXiv and Papers with Code websites have been making large headways in these spaces, bringing order from the chaos. In a recent collaboration, we now can enjoy integration between these services, as well as the benefit created from the combination of their data. The whole is definitely greater than the sum of the parts.