Tag: AI interpretability
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Reward-Lens: Interpretability Library for AI Reward Models
Discover Reward-Lens, an open-source library for mechanistic interpretability of AI reward models, enhancing transparency in reinforcement learning.
Explainable AI for Speaker Recognition: Understanding Clusters
Explore how Explainable AI reveals hierarchical clusters in speaker recognition, improving transparency and interpretability of neural network models.
Interpretable Diabetic Retinopathy Grading with CNN-Transformer Models
Discover how CNN-transformer ensembles improve diabetic retinopathy grading with visual explainability and vision-language model insights for clinical use.
Credal Concept Bottleneck Models for Uncertainty Decomposition
Explore Credal Concept Bottleneck Models that separate epistemic and aleatoric uncertainty for clearer AI predictions and better decision-making.
Atlas-Alignment: Scalable Interpretability for Language Models
Discover Atlas-Alignment, a framework that makes language model interpretability scalable, cost-efficient, and robust across AI systems.