2 papers
cs.CY2021
How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs?
Indira Sen, Mattia Samory, Fabian Floeck +2
As NLP models are increasingly deployed in socially situated settings such as online abusive content detection, it is crucial to ensure that these models are robust. One way of imp…
cs.LG2019
TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP
Nils Rethmeier, Vageesh Kumar Saxena, Isabelle Augenstein
While state-of-the-art NLP explainability (XAI) methods focus on explaining per-sample decisions in supervised end or probing tasks, this is insufficient to explain and quantify mo…