Explaining Pre-Trained Language Models with Attribution Scores: An Analysis in Low-Resource Settings

arXiv:2403.05338v1 Announce Type: new
Abstract: Attribution scores indicate the importance of different input parts and can, thus, explain model behaviour. Currently, prompt-based models are gaining popularity, i.a., due to their easier adaptability in low-resource settings. However, the quality of attribution scores extracted from prompt-based models has not been investigated yet. In this work, we address this topic by analyzing attribution scores extracted from prompt-based models w.r.t. plausibility and faithfulness and comparing them with attribution scores extracted from fine-tuned models and …

abstract adaptability analysis arxiv attribution cs.cl however importance language language models low prompt quality type