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article · IEEE BITS the Information Theory Magazine · 2023

Toward Textual Transform Coding

Tsachy Weissman

Cited by 6Abstract and details only

Abstract

Inspired by recent work on compression with and for humans, the success of transform-based approaches to information processing, and the rise of powerful language-based AI, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">textual transform coding</i> . It shares some of its key properties with traditional transform-based coding underlying much of our current multimedia compression technologies. It can form the basis for compression at bit rates until recently considered uselessly low, and for boosting human satisfaction from reconstructions at more traditional bit rates.

Cite this paper

APA 7

Weissman, T. (2023). Toward Textual Transform Coding. IEEE BITS the Information Theory Magazine, 3(2), 32–40. https://doi.org/10.1109/mbits.2023.3339111

MLA 9

Weissman, Tsachy. “Toward Textual Transform Coding.” IEEE BITS the Information Theory Magazine, vol. 3, no. 2, 2023, pp. 32–40, https://doi.org/10.1109/mbits.2023.3339111.

Chicago

Weissman, Tsachy. 2023. “Toward Textual Transform Coding.” IEEE BITS the Information Theory Magazine 3 (2): 32–40. https://doi.org/10.1109/mbits.2023.3339111.

Harvard

Weissman, T. (2023) ‘Toward Textual Transform Coding’, IEEE BITS the Information Theory Magazine, 3(2), pp. 32–40. Available at: https://doi.org/10.1109/mbits.2023.3339111.

BibTeX
@article{weissman2023toward,
  title = {{Toward Textual Transform Coding}},
  author = {Weissman, Tsachy},
  journal = {IEEE BITS the Information Theory Magazine},
  volume = {3},
  number = {2},
  pages = {32--40},
  year = {2023},
  doi = {10.1109/mbits.2023.3339111}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

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