Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

Processing 200,000 tokens through a large language model is expensive and slow: the longer the context, the faster the costs spiral. Researchers at Tsinghua University and Z.ai have built a technique ...

LDP consists of a diffusion modeling for encoded text space of an off-the-shelf pre-trained encoder and decoder, the diffusion process can be intervened by additional controller . Paraphrase ...

AlphaGenome is a leap forward in the ability to study the human blueprint. But the fine workings of our DNA are still largely a mystery. By Carl Zimmer In 2024, two scientists from Google DeepMind ...

READING, Pa.—Miri Technologies has unveiled the V410 live 4K video encoder/decoder for streaming, IP-based production workflows and AV-over-IP distribution, which will make its world debut at ISE 2026 ...

Gray codes, also known as reflected binary codes, offer a clever way to minimize errors when digital signals transition between states. By ensuring that only one bit changes at a time, they simplify ...

We present Representation Autoencoders (RAE), a class of autoencoders that utilize pretrained, frozen representation encoders such as DINOv2 and SigLIP2 as encoders with trained ViT decoders. RAE can ...

With so much money flooding into AI startups, it’s a good time to be an AI researcher with an idea to test out. And if the idea is novel enough, it might be easier to get the resources you need as an ...

Abstract: Small object detection (SOD) given aerial images suffers from an information imbalance across different feature scales. This makes it extremely challenging to perform accurate SOD. Existing ...