Grad-sam: Explaining transformers via gradient self-attention maps

O Barkan, E Hauon, A Caciularu, O Katz… - Proceedings of the 30th …, 2021 - dl.acm.org
Transformer-based language models significantly advanced the state-of-the-art in many
linguistic tasks. As this revolution continues, the ability to explain model predictions has …

Representation biases in sentence transformers

D Nikolaev, S Padó - arxiv preprint arxiv:2301.13039, 2023 - arxiv.org
Variants of the BERT architecture specialised for producing full-sentence representations
often achieve better performance on downstream tasks than sentence embeddings …

Counterfactual evaluation for explainable AI

Y Ge, S Liu, Z Li, S Xu, S Geng, Y Li, J Tan… - arxiv preprint arxiv …, 2021 - arxiv.org
While recent years have witnessed the emergence of various explainable methods in
machine learning, to what degree the explanations really represent the reasoning process …

Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps

E Hauon - 2023 - search.proquest.com
Transformer-based language models significantly advanced the state-of-the-art in many
linguistic tasks. As this revolution continues, the ability to explain model predictions has …