WassersteinGrad aggregates perturbed gradient attribution maps via their entropic Wasserstein barycenter to avoid blurring from geometric shifts in explanations of autoregressive weather forecasts.
Gradient based feature attribution in explainable ai: A technical review
5 Pith papers cite this work. Polarity classification is still indexing.
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AttnTrace is an attention-weight-based context traceback method for LLMs that claims higher accuracy and efficiency than prior art like TracLLM while aiding prompt injection detection.
The paper defines algorithmic contestability as identifying evidence to overturn potentially incorrect decisions and identifies three types of such evidence that make decisions normatively indefensible under the decision maker's standards.
Integrated gradients on a 10-class domestic sound classifier yields 0.39 mean IoU, 0.52 frame F1 and 82.6% Pointing Game accuracy for temporal event detection, approaching weakly and strongly supervised framewise CNN baselines.
citing papers explorer
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Explanation of Dynamic Physical Field Predictions using WassersteinGrad: Application to Autoregressive Weather Forecasting
WassersteinGrad aggregates perturbed gradient attribution maps via their entropic Wasserstein barycenter to avoid blurring from geometric shifts in explanations of autoregressive weather forecasts.
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AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption
AttnTrace is an attention-weight-based context traceback method for LLMs that claims higher accuracy and efficiency than prior art like TracLLM while aiding prompt injection detection.
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Explainable AI Isn't Enough! Rethinking Algorithmic Contestability
The paper defines algorithmic contestability as identifying evidence to overturn potentially incorrect decisions and identifies three types of such evidence that make decisions normatively indefensible under the decision maker's standards.
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Evaluating the Temporal Detection Capability of Integrated Gradients Applied on Sound Classifier
Integrated gradients on a 10-class domestic sound classifier yields 0.39 mean IoU, 0.52 frame F1 and 82.6% Pointing Game accuracy for temporal event detection, approaching weakly and strongly supervised framewise CNN baselines.
- Safety Must Precede the Deployment of Open-Ended AI