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This research outlines the LACOAT approach for enhancing deep neural network (DNN) prediction explanations through latent concept-based methods. It addresses existing limitations by leveraging contextual facets of words, clustering features into latent concepts, and attributing predictions to these inputs. Key components include ConceptDiscoverer, PredictionAttributor, ConceptMapper, and PlausiFyer tools for comprehensive insight. Experimental evaluations on POS tagging and sentiment analysis...