The baseline methods have utilized contrastive learning yet they fail to account for negative sample misclassification, and they design separate encoders per modality without considering the ...

To train the models, Apple broke the recordings into short 5-second clips, moving forward one second at a time. That added up ...

Moreover, the traditional transformer-based MAE is applied as an auxiliary branch, and contrastive learning is utilized on the features extracted from the encoders of both MAEs. This auxiliary branch ...

To bridge this gap, we introduce DICE: Device-level Integrated Circuits Encoder—the first graph neural network ... DICE adopts a simulation-free pretraining approach based on graph contrastive ...

This project implements a pipeline for clustering tweets from the TweetEval dataset (emotion subset) using a custom BERT-based encoder with a contrastive learning approach. The model fine-tunes a BERT ...

Humans naturally learn by making connections between sight and sound. For instance, we can watch someone playing the cello ...

A vision encoder is a necessary component for allowing many leading LLMs to be able to work with images uploaded by users.