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

Robust Blind Watermarking to Secure Color Medical Images Using Multidimensional-FFT Fusing LFSR-Encryption and LZW Compression

Abstract: This paper offers a new robust-blind watermarking scheme for medical image protection. In the digital era, protecting medical images is essential to maintain the confidentiality of patients ...
GitHub

zstd_compress_sequences.h

/* SPDX-License-Identifier: GPL-2.0+ OR BSD-3-Clause */ * Copyright (c) Meta Platforms, Inc. and affiliates. * All rights reserved. * This source code is licensed ...
marktechpost

Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google’s TurboQuant Algorithm

Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million document embeddings in float32 consumes 31 GB of RAM. For dev teams running ...
marktechpost

A Coding Implementation to Compress and Benchmark Instruction-Tuned LLMs with FP8, GPTQ, and SmoothQuant Quantization using llmcompressor

In this tutorial, we explore how to apply post-training quantization to an instruction-tuned language model using llmcompressor. We start with an FP16 baseline and then compare multiple compression ...
IEEE

4D Memristive Hyperchaotic System for Secure Image Encryption Using Non-Associative Algebraic-Chaotic Sequences

Abstract: The potential of discrete memristors to improve chaotic systems for safe communication has been demonstrated by recent advancements. This paper presents a novel four-dimensional (4D) ...