When comparing compression ratios in serious publications, it is customary to include the size of the decompression utility and any dictionaries required for de

When comparing compression ratios in serious publications, it is customary to include the size of the decompression utility and any dictionaries required for decompression in one's numbers, especially where these are of comparable size to the corpus used for testing or larger. It is otherwise trivial to come up with compression schemes that show amazing performance on some corpus, simply by smuggling arbitrarily large parts of the corpus inside the decompression utility. In this case, the entire, exact large language model dataset used to compress the data is required for decompression. Since this is not accounted for, the paper is meaningless. Note that there are prizes available for genuine AI based improvements to English text compression, e.g. https://en.wikipedia.org/wiki/Hutter_Prize https://en.wikipedia.org/wiki/Hutter_Prize