Summarization Scaling is a new technique for summarization that has been made possible thanks to LLMs like GPT 3.5 and Claude 2. These tools can provide summaries of text. These summaries can be a variety of lengths. Summarization Scaling is the practice of prompting an LLM for summaries of multiple sizes and allowing the user to increase or decrease the size of an article summary as desired.
Inspired by https://www.instagram.com/reel/CzHUjt1Pjgf/?igshid=MzRlODBiNWFlZA==
Semantic pinch to zoom: https://twitter.com/hturan/status/1776225700954939608?t=2UES8Jaz9txDnBd5scuXtw&s=19
See also: https://en.m.wikipedia.org/wiki/StretchText https://x.com/DefenderOfBasic/status/1806048482823721086?t=YBIpiY50mDqjENaWgIy_dw&s=19