Papers with vanilla self-attention module

1 papers
Efficient Classification of Long Documents via State-Space Models (2023.emnlp-main)

Copied to clipboard

Challenge: Existing transformer-based models can only process long documents with limited computational resources due to their quadratic computation time and space.
Approach: They propose to use state-space models for long document classification tasks instead of using sparse or hierarchical structures to solve this problem.
Outcome: The proposed model performs comparable to self-attention models while being 36% more efficient.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations