Research

Wikipedia, the world’s largest online encyclopedia, relies on a massive community of volunteers to maintain its accuracy and neutrality. But with so many editors, how do you ensure edits adhere to Wikipedia’s strict policies? I decided to explore whether Large Language Models (LLMs) could be used to automatically detect policy violations in Wikipedia edits. Here’s what I found. Wikipedia has well-defined policies to ensure content quality. These include: WP:NPOV (Neutral Point of View): Avoiding bias and presenting information objectively. [Read More]

This is a blog post version a paper titled “Question-to-Question Retrieval for Hallucination-Free Knowledge Access: An Approach for Wikipedia and Wikidata Question Answering” available at https://arxiv.org/abs/2501.11301. In the world of Large Language Models (LLMs) and question answering systems, hallucination - where models generate plausible but incorrect information - remains a significant challenge. This is particularly problematic when dealing with encyclopedic knowledge sources like Wikipedia, where accuracy is paramount. Today, I’ll discuss a novel approach that addresses this challenge through question-to-question retrieval. [Read More]