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Large pre-trained language models have become popular for many applications and form an important backbone of many downstream tasks in natural language processing (NLP). Applying 'explainable artificial intelligence' (XAI) techniques to enrich such m
Externí odkaz:
http://arxiv.org/abs/2406.11547
Autor:
Clark, Benedict, Wilming, Rick, Dox, Artur, Eschenbach, Paul, Hached, Sami, Wodke, Daniel Jin, Zewdie, Michias Taye, Bruila, Uladzislau, Oliveira, Marta, Schulz, Hjalmar, Cornils, Luca Matteo, Panknin, Danny, Boubekki, Ahcène, Haufe, Stefan
The evolving landscape of explainable artificial intelligence (XAI) aims to improve the interpretability of intricate machine learning (ML) models, yet faces challenges in formalisation and empirical validation, being an inherently unsupervised proce
Externí odkaz:
http://arxiv.org/abs/2405.12261