LLMZip: Lossless Text Compression using Large Language Models
Authors: name: Chandra Shekhara Kaushik Valmeekam, name: Krishna Narayanan, name: Dileep Kalathil, name: Jean-Francois Chamberland, name: Srinivas Shakkottai

We provide new estimates of an asymptotic upper bound on the entropy of
English using the large language model LLaMA-7B as a predictor for the next
token given a window of past tokens. This estimate is significantly smaller
than currently available estimates in cover1978convergent,
lutati2023focus. A natural byproduct is an algorithm for lossless
compression of English text which combines the prediction from the large
language model with a lossless compression scheme. Preliminary results from
limited experiments suggest that our scheme outperforms state-of-the-art text
compression schemes such as BSC, ZPAQ, and paq8h.