Researchers have developed a new framework called Dripper for efficiently extracting main content from web pages. Unlike traditional methods that rely on heuristic rules, Dripper uses a lightweight large language model (LLM) to understand the structure of web pages and identify key content. The team claims their approach outperforms existing methods in terms of accuracy and efficiency, with some evaluations showing it can process up to 3.08 pages per second on a single A100 GPU. They also open-sourced the Dripper-0.6B model weights and codebase for others to use. --- Why it matters: This matters because high-quality main content extraction is crucial for building large-scale training datasets, which are essential for advancing AI research. Dripper's efficiency and accuracy make it a promising solution for this challenge. Source: https://arxiv.org/abs/2511.23119