Making LLMs Cite Their Sources: A Plain-English Guide to Evidence-Based Text Generation For developers, product managers, and curious readers who want AI answers they can trust. 1. Why Should I Care If My AI “Shows Its Work”? Quick scenario: You ask an AI chatbot, “Will Spain’s population hit 48 million by 2025?” It answers “Yes,” but offers no proof. You’re left wondering: Is this real or just another confident hallucination? Evidence-based text generation solves this exact problem. Instead of a bare answer, the model returns traceable references—links, footnotes, or direct quotes—so you can check every claim. A new survey from …
Evidence-Based Text Generation with Large Language Models: A Systematic Study of Citations, Attributions, and Quotations In the digital age, large language models (LLMs) have become increasingly widespread—powering everything from customer service chatbots to content creation tools. These models are reshaping how humans process and generate text, but their growing popularity has brought a critical concern to the forefront: How can we trust the information they produce? When an LLM generates an analysis report, an academic review, or a key piece of information, how do we verify that the content is supported by solid evidence? And how can we trace the …