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arxiv: 2306.04050 · v2 · pith:JOPDBC2U · submitted 2023-06-06 · cs.IT · cs.CL· cs.LG· math.IT

LLMZip: Lossless Text Compression using Large Language Models

Chandra Shekhara Kaushik Valmeekam , Krishna Narayanan , Dileep Kalathil , Jean-Francois Chamberland , Srinivas Shakkottai This is my paper

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classification cs.IT cs.CLcs.LGmath.IT
keywords compressionlanguagelargelosslesstextciteenglishestimates
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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 \cite{cover1978convergent}, \cite{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.

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