Search Results for author:
Found 2 papers, 0 papers with code
Memory in humans and deep language models: Linking hypotheses for model augmentation
The computational complexity of the self-attention mechanism in Transformer models significantly limits their ability to generalize over long temporal durations.
Slower is Better: Revisiting the Forgetting Mechanism in LSTM for Slower Information Decay
Altogether, we found that LSTM with the proposed forget gate can learn long-term dependencies, outperforming other recurrent networks in multiple domains; such gating mechanism can be integrated into other architectures for improving the learning of long timescale information in recurrent neural networks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
