Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

Probability underlies much of the modern world – an engineering professor explains how it actually works

Probability underpins AI, cryptography and statistics. However, as the philosopher Bertrand Russell said, “Probability is the ...

Scientists solve one of the most notorious open problems in math

It’s a breakthrough in the field of random walks.
IEEE

Circuit lines for guiding the generation of random test sequences for synchronous sequential circuits

Abstract: A procedure proposed earlier for improving the fault coverage of a random primary input sequence modifies the input sequence so as to avoid repeated synchronization of state variables. We ...
GitHub

Fine-tuning sequence-to-expression models on personal genome and transcriptome data

The code base for our work on improving the performance of sequence-to-expression models for making individual-specific gene expression predictions by fine-tuning them on personal genome and ...
IEEE

MIMO Radar System Based on Physical Random Code for 3D Multi-Target Imaging

Abstract: A physical random code (PRC) multiple-input multiple-output (MIMO) radar system is proposed and experimentally demonstrated for three-dimensional (3D) multi-target imaging. The radar system ...
GitHub

Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion

@article{chen2025diffusion, title={Diffusion forcing: Next-token prediction meets full-sequence diffusion}, author={Chen, Boyuan and Mart{\'\i} Mons{\'o}, Diego and ...