Papers by Jason Kuen

2 papers
Learning Adaptive Axis Attentions in Fine-tuning: Beyond Fixed Sparse Attention Patterns (2022.findings-acl)

Copied to clipboard

Challenge: Adaptive Axis Attention learns different attention patterns for each task and model layer . sparse attention patterns do not improve the run time of the models but they reduce model memory requirements .
Approach: They propose a method that learns different attention patterns for each Transformer layer . they propose 'adaptive axis attention' method that identifies important tokens .
Outcome: The proposed method does not require pre-training to accommodate sparse attention patterns.
A Critical Analysis of Document Out-of-Distribution Detection (2023.findings-emnlp)

Copied to clipboard

Challenge: Existing document understanding models focus on single-modal inputs such as images or texts.
Approach: They propose to use a spatial-aware adapter to adapt transformer-based language models to document domain to exploit multi-modal information.
Outcome: The proposed model significantly improves the OOD detection performance compared to using a standard language model and to competitive baselines.

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