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Google researchers address the challenges of achieving a comprehensive understanding of diverse video content by introducing a novel encoder model, VideoPrism. Existing models in video understanding…
There has been notable progress in Vision-Language tasks, with models like CLIP showing impressive performance in various tasks. While these models excel at recognizing objects, they…
Using scenario based stress testing to identify medium (2050) and long term (2100) sea level rise risksThis project utilizes a scenario based qualitative stress testing approach…
In machine learning, the effectiveness of tree ensembles, such as random forests, has long been acknowledged. These ensembles, which pool the predictive power of multiple decision…
First of all, let’s define our hypoparameters. Like in many other metaheuristic algorithms, these variables should be adjusted on the way, and there is no versatile…
The ability to predict outcomes from a myriad of parameters has traditionally been anchored in specific, narrowly focused regression methods. While effective within its domain, this…
When LLMs give us outputs that reveal flaws in human society, can we choose to listen to what they tell us?Photo by Vince Fleming on UnsplashBy…
Point clouds serve as a prevalent representation of 3D data, with the extraction of point-wise features being crucial for various tasks related to 3D understanding. While…
The CHiME-8 MMCSG task focuses on the challenge of transcribing conversations recorded using smart glasses equipped with multiple sensors, including microphones, cameras, and inertial measurement units…
In robotics, natural language is an accessible interface for guiding robots, potentially empowering individuals with limited training to direct behaviors, express preferences, and offer feedback. Recent…