Titlebook: Explainable Artificial Intelligence; First World Conferen Luca Longo Conference proceedings 2023 The Editor(s) (if applicable) and The Auth

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书目名称Explainable Artificial Intelligence影响因子(影响力)




书目名称Explainable Artificial Intelligence影响因子(影响力)学科排名




书目名称Explainable Artificial Intelligence网络公开度




书目名称Explainable Artificial Intelligence网络公开度学科排名




书目名称Explainable Artificial Intelligence被引频次




书目名称Explainable Artificial Intelligence被引频次学科排名




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书目名称Explainable Artificial Intelligence年度引用学科排名




书目名称Explainable Artificial Intelligence读者反馈




书目名称Explainable Artificial Intelligence读者反馈学科排名

Lacerate

Natural Example-Based Explainability: A Surveyng models. While saliency maps have stolen the show for the last few years in the XAI field, their ability to reflect models’ internal processes has been questioned. Although less in the spotlight, example-based XAI methods have continued to improve. It encompasses methods that use examples as expla

白杨鱼

Presbyopia

Contrastive Visual Explanations for Reinforcement Learning via Counterfactual Rewardsive explanation framework for reinforcement learning (RL) based on comparing learned policies under actual environmental rewards vs. hypothetical (counterfactual) rewards. The framework provides policy-level explanations by accessing learned Q-functions and identifying intersecting critical states.

STALE

共同确定为确

共同确定为确

A Novel Architecture for Robust Explainable AI Approaches in Critical Object Detection Scenarios Basritical situations. We provide a novel approach focusing on potential edge cases in order to address those specific situations which are often most the hardest part in bringing machine learning models into production within the aforementioned scenarios. We improve upon existing explainable artificia

aspect

Jocose

exorbitant

The Duet of Representations and How Explanations Exacerbate Itwith the human’s prior belief. Explanations can direct the human’s attention to the conflicting feature and away from other relevant features. This leads to causal overattribution and may adversely affect the human’s information processing. In a field experiment we implemented an XGBoost-trained mod