Journal Articles
If I were to ask you what your go to form of content to consume is, you probably wouldn’t respond with “Uh, easy, journal articles”. I mean the lack of humor is the first major problem and without that immediate dopamine hit that other forms of content like TicTok provide, it can be difficult to stay engaged. But if you actually think hard about it, journal articles fix all the problems that traditional social media has. There’s no clickbait, they literally summarize the information for you, and there is an incredible diversity of information. Honestly, I would be surprised if ArXiv doesn’t become the next TicTok.
On a more serious note though, I have found that if you are genuinely interested in an academic field, journal articles provide a wealth of resources that is truly irreplaceable. Especially for a field like AI, journal articles are an excellent (and honestly almost required) way to keep up with the breakneck speed of AI research. Personally, published papers have probably been the most helpful way for me to develop specialized interests in AI (particularly my computational-social-sciency and philosophical interest), since most other sources of information either don’t go into the necessary detail or aren’t up to date with current research.
Whether you want to get an in depth understanding of topics in AI or are a wanna-be-know-it-all who should really get his facts straight (talking to you big brother), I will be using this page to post resources to find articles, articles that I found very interesting, and articles that were helpful in my understanding in key AI topics.
*When I say published academic articles I am including articles on ArXiv
Resources
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Reddit
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ArXiv
Journal Articles
We Don’t Speak the Same Language: Interpreting Polarization Through Machine Translation
Mining Insights from Large-scale Corpora Using Fine-tuned Language Models
Word embeddings quantify 100 years of gender and ethnic stereotypes
A Formalization of Kant's Second Formulation of the Categorical Imperative
Towards A Rigorous Science of Interpretable Machine Learning
Achieving Fairness in Determining Medicaid Eligibility through Fairgroup Construction
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Enriching Word Vectors with Subword Information
Offline bilingual word vectors, orthogonal transformations and the inverted softmax
Systematic Inequalities in Language Technology Performance across the World’s Languages