Papers with uncertainty measures

2 papers
The Role of Context and Uncertainty in Shallow Discourse Parsing (2022.coling-1)

Copied to clipboard

Challenge: Discourse parsing has proven to be useful for a number of NLP tasks that require complex reasoning.
Approach: They hypothesize that context plays an important role in accurate human annotation and add uncertainty measures can improve model accuracy and calibration.
Outcome: The proposed model can be better calibrated by adding uncertainty measures to models with better accuracy and calibration.
Investigating the Impact of Model Instability on Explanations and Uncertainty (2024.findings-acl)

Copied to clipboard

Challenge: Explainable AI methods are typically evaluated holistically, but small perturbations to inputs can vastly distort explanations.
Approach: They artificially simulate epistemic uncertainty in text input by introducing noise at inference time and measure the effect on the output of pre-trained language models.
Outcome: The proposed model can detect salient tokens when uncertain, but it is not reliable when small perturbations are exposed during training.

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