The Three Oldest Pillars of NLP Author Dhruv Gupta ( ORCID : 0009–0004–7109–5403) Introduction Natural Language Processing (NLP) has almost become synonymous with Large Language Models (LLMs), Generative AI, and fancy chatbots. With the ever-increasing amount of textual data and exponential growth in computational knowledge, these models are improving every day.

Understanding the Power and Applications of Natural Language Processing Author Dhruv Gupta ( ORCID: 0009–0004–7109–5403) Introduction We are living in the era of generative AI. In an era where you can ask AI models almost anything, they will most certainly have an answer to the query. With the increased computational power and the amount of textual data, these models are bound to improve their performance.

Last week, a paper I wrote on the subject of peer-review fraud was published in the journal Scientometrics (free link here, preprint here) . It was an interesting project to work on. I found a lot of examples where one referee would write a report during peer-review and then another referee would write an identical report in some other peer-review of some other paper.

This post is about The Papermill Alarm: an API for detecting potential papermill-products. There’s a field of study called ‘stylometry’ where we look at the statistical properties of someone’s writing and use that to model their ‘style’. People write in idiosyncratic ways.

I once saw a brilliant presentation about how simple data analysis can detect credit card fraud**. The presentation showed a pattern in how people use their credit cards. Given a large number of people who had been victims of credit card fraud, this pattern showed there was just 1 store in-particular where they had all used their cards. There was no observational evidence of someone at that store stealing card details.