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.

Open-source FLIM Playground could speed reproducible analysis of complex cell images

Modern fluorescence microscopy can generate images of living cells as stunning to look at as they are informative to study. For techniques like fluorescence lifetime imaging microscopy (FLIM), those ...
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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