Earlier quoted context omitted.
Right, so in total ignorance what I would do is just make a GPT powered text compressor and decompressor using a range coder with its probabilities at each token set by the model. Care would need to be taken with precision and end termination so a bias wouldn't be introduced (more care than typical in compressors, since no one normally cares much about 0.01% inefficiencies-- things like end termination have been addr…
Hi, I am one of the authors on the PSSuMEC paper. Thanks a lot for your interest in our work. If I understand correctly, range coding would have the same lack of perfect security properties as arithmetic coding (cf our paper). Having said this, we are investigating the utility of iMEC in compression settings.
It might just be that the precision rapidly becomes unmanageable, because I guess you need to support the least probable symbol from every token without ever losing precision (normally arithmetic coders will re-normalize after each symbol to keep the accumulator in a reasonable precision, though they could be designed to do so as infrequently as you like at a performance cost)... If no renormalization is possible I guess an arithmetic coder accumulator would need to handle values like (1/least_prob_token)^n_tokens which gets extremely big extremely fast -- and would at the very least need an unconventional construction.