Papers by Jakob Havtorn

1 papers
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records (2024.emnlp-main)

Copied to clipboard

Challenge: State-of-the-art explainability methods rely on human annotations, which are costly.
Approach: They propose an approach to produce plausible and faithful explanations without annotations . they use adversarial robustness training to improve plausibility and AttInGrad .
Outcome: The proposed method produces plausible explanations without human annotations on a medical coding task.

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