Abstract: We establish that it is possible to extract accurate blockwise and bitwise soft output (SO) from Guessing Codeword Decoding (GCD) with minimal additional computational complexity by ...

IntroductionAPT37 (also known as ScarCruft, Ruby Sleet, and Velvet Chollima) is a North Korean-aligned threat actor active since at least 2012. APT37 primarily targets South Korean individuals ...

Abstract: In this letter, we present an improved ternary message passing (TMP) decoding scheme designed for the high-rate regular low-density parity-check (LDPC) codes, which are widely used in ...

We have 2 PhD positions for international students at Westlake University, China! see here. We provide the pre-trained Evolla-10B model in huggingface hub. You can ...

QUEEN (QUantized Efficient ENcoding) is a novel framework for efficient, streamable free-viewpoint video (FVV) representation using dynamic 3D Gaussians. QUEEN enables high-quality dynamic scene ...

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If you’ve ever taken even a cursory glance at a hurricane forecast, you’ve seen some version of the “cone of uncertainty.” It sounds like some other-dimensional realm of indecision, but it’s a ...

Written in Rust, the PyApp utility wraps up Python programs into self-contained click-to-run executables. It might be the easiest Python packager yet. Every developer knows how hard it is to ...

Surgically implanted devices that allow paralyzed people to speak can also eavesdrop on their inner monologue. That's the conclusion of a study of brain-computer interfaces (BCIs) in the journal Cell.

A new study out this month from Stanford University researchers uses microelectrodes implanted in the motor cortex and generative AI to decode the intended and inner speech of four paralyzed patients.