Papers › Lossless data compression by large models

Lossless data compression by large models

24 Jun 2024arXiv:2407.07723archive 2025-07-28

Ziguang Li, Chao Huang, Xuliang Wang, Haibo Hu, Cole Wyeth, Dongbo Bu, Quan Yu, Wen Gao, Xingwu Liu, Ming Li

Modern data compression methods are slowly reaching their limits after 80 years of research, millions of papers, and wide range of applications. Yet, the extravagant 6G communication speed requirement raises a major open question for revolutionary new ideas of data compression. We have previously shown all understanding or learning are compression, under reasonable assumptions. Large language models (LLMs) understand data better than ever before. Can they help us to compress data? The LLMs may be seen to approximate the uncomputable Solomonoff induction. Therefore, under this new uncomputable paradigm, we present LMCompress. LMCompress shatters all previous lossless compression algorithms, doubling the lossless compression ratios of JPEG-XL for images, FLAC for audios, and H.264 for videos, and quadrupling the compression ratio of bz2 for texts. The better a large model understands the data, the better LMCompress compresses.

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load_dataframes mcGill-NLP/medal/utils.py official repository ran no licence file found · pointer only · cba10c551fb3c323 · report
load_mimic_mortality mcGill-NLP/medal/downstream/utils.py official repository ran no licence file found · pointer only · 8155689bc5957966 · report
load_model mcGill-NLP/medal/utils.py official repository ran no licence file found · pointer only · 0c2a1f556b1e44d6 · report
lstm mcGill-NLP/medal/hubconf.py official repository ran no licence file found · pointer only · ef7adb5972287dde · report
lstm_sa mcGill-NLP/medal/hubconf.py official repository ran no licence file found · pointer only · 22270589c7ec7481 · report
prepare_label mcGill-NLP/medal/downstream/tokenizer_and_dataset.py official repository ran no licence file found · pointer only · eb090d26e716d944 · report
electra mcGill-NLP/medal/hubconf.py official repository unverified no licence file found · pointer only · 71a9ba6b952ddf00 · report
evaluate mcGill-NLP/medal/utils.py official repository unverified no licence file found · pointer only · ba02ce5ab3059cd9 · report
load_mimic_diagnosis mcGill-NLP/medal/downstream/utils.py official repository unverified no licence file found · pointer only · 9de277840306a450 · report

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