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Explainable Information Retrieval: A Survey
Explainable information retrieval is an emerging research area aiming to make transparent and trustworthy information retrieval systems.
Towards Benchmarking the Utility of Explanations for Model Debugging
Post-hoc explanation methods are an important class of approaches that help understand the rationale underlying a trained model's decision.
Multimodal Analytics for Real-world News using Measures of Cross-modal Entity Consistency
In this paper, we introduce a novel task of cross-modal consistency verification in real-world news and present a multimodal approach to quantify the entity coherence between image and text.
Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases
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.
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