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pro vyhledávání: '"Idahl, Maximilian"'
Explainable information retrieval is an emerging research area aiming to make transparent and trustworthy information retrieval systems. Given the increasing use of complex machine learning models in search systems, explainability is essential in bui
Externí odkaz:
http://arxiv.org/abs/2211.02405
Post-hoc explanation methods are an important class of approaches that help understand the rationale underlying a trained model's decision. But how useful are they for an end-user towards accomplishing a given task? In this vision paper, we argue the
Externí odkaz:
http://arxiv.org/abs/2105.04505
The World Wide Web has become a popular source for gathering information and news. Multimodal information, e.g., enriching text with photos, is typically used to convey the news more effectively or to attract attention. Photo content can range from d
Externí odkaz:
http://arxiv.org/abs/2003.10421
In this paper we propose and study the novel problem of explaining node embeddings by finding embedded human interpretable subspaces in already trained unsupervised node representation embeddings. We use an external knowledge base that is organized a
Externí odkaz:
http://arxiv.org/abs/1910.05030
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