Wednesday, June 19, 2024

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I tested out a...

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Meta has created a system that can embed hidden signals, known as...

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Why does AI hallucinate?

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Diffusion Models as Masked Audio-Video Learners



This paper was accepted at the Machine Learning for Audio Workshop at NeurIPS 2023.
Over the past several years, the synchronization between audio and visual signals has been leveraged to learn richer audio-visual representations. Aided by the large availability of unlabeled videos, many unsupervised training frameworks have demonstrated impressive results in various downstream audio and video tasks. Recently, Masked Audio-Video Learners (MAViL) has emerged as a state-of-the-art audio-video pre-training framework. MAViL couples contrastive learning with masked autoencoding to jointly…



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Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials

In practice, training using federated learning can be orders of magnitude slower than standard centralized training. This severely limits the amount of experimentation and tuning that can be done, making it challenging to obtain good performance on a...

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024 Article Source link and Credit

Introducing Apple’s On-Device and Server Foundation Models

Introducing Apple’s On-Device and Server Foundation Models Article Source link and Credit