2 citations · 3 across the 3 of their papers we have counts for
4 papers
On the Impact of Temporal Concept Drift on Model Explanations
Zhixue Zhao, George Chrysostomou, Kalina Bontcheva +1
Explanation faithfulness of model predictions in natural language processing is typically evaluated on held-out data from the same temporal distribution as the training data (i.e.…
An Empirical Study on Explanations in Out-of-Domain Settings
George Chrysostomou, Nikolaos Aletras
Recent work in Natural Language Processing has focused on developing approaches that extract faithful explanations, either via identifying the most important tokens in the input (i…
Frustratingly Simple Pretraining Alternatives to Masked Language Modeling
Atsuki Yamaguchi, George Chrysostomou, Katerina Margatina +1
Masked language modeling (MLM), a self-supervised pretraining objective, is widely used in natural language processing for learning text representations. MLM trains a model to pred…
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification
George Chrysostomou, Nikolaos Aletras
Neural network architectures in natural language processing often use attention mechanisms to produce probability distributions over input token representations. Attention has empi…