Utilizing mutual learning can effectively enhance the performance of peer BNNs.

In this paper, we adapt Mamba, a state-space language model, into VMamba, a vision backbone with linear time complexity.

In our experiments, the proposed method achieved a test classification accuracy of 96.5%

Second, generalization--what specific aspects of the transformer architecture are responsible for their effective learning?

Neural Information Processing Systems http://nips.cc/

In each competition, numerous practitioners repeatedly evaluated their progress against a holdout set that forms the basis of a public ranking availablethroughout the competition. Performance on a separate test set used only oncedetermined the final ranking.