Recent studies have shown promising results on utilizing large pre-trained image-language models for video question answering.

In image classification, it is common to utilize a pretrained model to extract meaningful features of the input images, and then to train a classifier on top of it to make predictions for any downstream task.

We explored whether SSL performance systematically varied as a function of reverberance using acoustic simulations.

Here, we present the VCL Benchmark: the first large-scale dataset for benchmarking SSL algorithms in rodents.

However, a topology with a fast consensus rate, e.g., the exponential graph, generally has a large maximum degree, which incurs significant communication