2 papers
cs.CL2026
Diffuse to Compress: Leveraging Diffusion LMs for Lossless Compression
Angelo Nardone, Paolo Ferragina
We study the problem of lossless text compression, motivated by the rapid growth in the collection and storage of digital textual data - including plain text, source code, and stru…
cs.IT2026
LLM-based Source Code Compression via Thresholded Symbol Ranking
Angelo Nardone, Paolo Ferragina
We study the problem of lossless compression of source code, motivated by the storage demands of large-scale software archives, such as Software Heritage (https://www.softwareherit…