深度神经网络能否突破极限，为超大规模科学数据压缩带来革命性提升？这篇arXiv新研究直击核心问题。
arXiv:2606.14353v1 Announce Type: new Abstract: Error-bounded lossy compression is a fundamental technique for managing the rapidly growing volumes of…
流式草图技术将1亿事件压至93KB，极致压缩比令人惊叹。
https://github.com/SBALAVIGNESH123/sketchlog Comments URL: https://news.ycombinator.com/item?id=48507112 Points: 1 # Comments: 0
为以太坊数据量身打造的结构化编码层，比经典ZSTD压缩再提升12-21%，区块链节点同步更快更省带宽
Article URL: https://github.com/Louw115/nep-ethereum-compression Comments URL: https://news.ycombinator.com/item?id=48420973 Points: 3 # Comments: 1
提出Float8@2bits方法，用熵编码在无数据场景下高效压缩模型，性能几乎无损。
arXiv:2601.22787v2 Announce Type: replace Abstract: Post-training compression is currently divided into two contrasting regimes. On the one hand, fast…
探明压缩推理数据在LLM后训练中的生效条件与方式，为效率优化提供理论支撑。
arXiv:2605.28008v1 Announce Type: new Abstract: Large language models (LLMs) can now solve complex problems through long chain-of-thought (CoT) reason…