Google’s Recommender System Breakthrough Detects Semantic Intent

Google quietly published a research paper on personalized semantics for recommender systems like Google Discover and YouTube.
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Word2Vec from scratch: Training word embeddings explained part 1

In this video, we will learn about training word embeddings. To train word embeddings, we need to solve a fake problem. This ...
IEEE

Timestep Embedding Tells: It’s Time to Cache for Video Diffusion Model

Abstract: As a fundamental backbone for video generation, diffusion models are challenged by low inference speed due to the sequential nature of denoising. Previous methods speed up the models by ...
IEEE

A Lightweight Semantic Segmentation Network Based on Self-Attention Mechanism and State Space Model for Efficient Urban Scene Segmentation

Abstract: In the semantic segmentation of remote sensing images, methods based on convolutional neural networks (CNNs) and Transformers have been extensively studied. Nevertheless, CNN struggles to ...