Shapley values for assessing research production and impact of schools and scholars
PulseAugur coverage of Shapley values for assessing research production and impact of schools and scholars — every cluster mentioning Shapley values for assessing research production and impact of schools and scholars across labs, papers, and developer communities, ranked by signal.
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New contrastive explanations for AI argumentation frameworks unveiled
Researchers have introduced contrastive explanations for Quantitative Bipolar Argumentation Frameworks (QBAFs), a method for explaining the differences between two arguments rather than just one. This new approach defin…
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QuadraSHAP offers stable, scalable Shapley values for product games
Researchers have developed QuadraSHAP, a novel method for efficiently calculating Shapley values in product games, which are common in machine learning explainability. The technique reduces the complex calculation to a …
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Quadrature-TreeSHAP offers faster, more stable AI model explanations
Researchers have developed Quadrature-TreeSHAP, a novel method for explaining tree ensemble predictions that is depth-independent and more numerically stable than existing approaches. This new technique extends naturall…
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New statistical viewpoint improves probabilistic value estimation for AI
Researchers have developed a new statistical viewpoint for understanding and improving probabilistic value estimation methods. Their work identifies a common first-order error structure across existing estimators, which…
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New framework uses K-Shapley values for meritocratic fairness in bandits
Researchers have introduced a novel framework for achieving meritocratic fairness in budgeted combinatorial multi-armed bandits with full-bandit feedback. This new approach extends the Shapley value concept to a K-Shapl…
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Researchers develop Shapley value explainers for temporal graph neural networks
Researchers have developed two new model-agnostic explainers for Temporal Graph Neural Networks (TGNNs), utilizing Shapley and Owen values. These methods aim to make the predictions of TGNNs, which combine spatial and t…
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Study finds Shapley value benchmarks for AI explainability misaligned with human utility
A new paper examines the evaluation of explainable AI (XAI) methods, specifically Shapley value variants, in high-stakes scenarios like fraud detection. Researchers found that standard quantitative metrics for XAI do no…