Turri, V., Schieber, N., Loughin, C., and Brooks, T., 2026: The ELM Library: An LLM Evaluation Toolset. Software Engineering Institute blog, Accessed June 24, 2026 ...

This is the official implementation of our paper TFMQ-DM, a novel training-free framework that achieves a new state-of-the-art result in PTQ of diffusion models, especially under 4-bit weight ...

If VRAM is the brake pedal on local LLMs, quantization is how we ease the pressure. At its core, it’s simple: store numbers with fewer bits. But in practice, modern methods like GPTQ, AWQ, and GGUF ...

The right Python libraries can dramatically improve speed, efficiency, and maintainability in 2025 projects. Mastering a mix of data, AI, and web-focused libraries ensures adaptability across multiple ...

Discovering new functional crystalline materials through computational methods remains a challenge in materials science. We introduce VQCrystal, a deep learning framework leveraging discrete latent ...

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OmniServe aims to revolutionize large-scale LLM serving by unifying and optimizing key advancements in both low-bit quantization and long-context processing. OmniServe integrates the innovations from ...

Running large language models (LLMs) like ChatGPT and Claude usually involves sending data to servers managed by OpenAI and other AI model providers. While these services are secure, some businesses ...

Liquid State Machines (LSMs) are computing reservoirs composed of recurrently connected Spiking Neural Networks which have attracted research interest for their modeling capacity of biological ...

Flow cytometry is broadly used in biomedicine, which is exemplified by identification of protein marker expressions 1,2,3,4,5,6, determinations of cell-fate and cell cycle progression 7, analysis of ...