Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit

LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.
IEEE

Reversible Data Hiding in Encrypted Images Based on Multi-MSB Prediction and Huffman Coding

Abstract: With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) has attracted increasing attention as a technology that can: embed additional ...
GitHub

Awesome - Most Cited Deep Learning Papers

[Notice] This list is not being maintained anymore because of the overwhelming amount of deep learning papers published every day since 2017. A curated list of the most cited deep learning papers ...
IEEE

Vulnerability Prediction From Source Code Using Machine Learning

Abstract: As the role of information and communication technologies gradually increases in our lives, software security becomes a major issue to provide protection against malicious attempts and to ...
GitHub

Von Nikolo N. Palermo rottiecode

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