Lossless Compression

Lossless compression aims to reduce data size without information loss, a crucial task for managing ever-growing datasets across various domains. Current research emphasizes leveraging deep learning models, particularly large language models (LLMs) and neural networks, often incorporating techniques like autoregressive modeling, transformers, and vector quantization, to achieve superior compression ratios compared to traditional algorithms. These advancements are significant for improving storage efficiency, reducing transmission costs, and enabling the practical use of massive datasets in fields ranging from scientific computing to medical imaging and natural language processing.