2 papers
cs.IT2026
Investigating the Fundamental Limit: A Feasibility Study of Hybrid-Neural Archival
Marcus Armstrong, ZiWei Qiu, Huy Q. Vo +1
Large Language Models (LLMs) possess a theoretical capability to model information density far beyond the limits of classical statistical methods (e.g., Lempel-Ziv). However, utili…
cs.DC2025
Boosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration
Shixun Wu, Jinwen Pan, Jinyang Liu +8
As high-performance computing architectures evolve, more scientific computing workflows are being deployed on advanced computing platforms such as GPUs. These workflows can produce…