glossary termAngestromTrust 60Published 3mo agoLive · 2mo ago
Inference
Running a trained model to get predictions.
Running a trained model to get predictions. Running a trained model to get predictions.
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- LinkedLinked via unknownReliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models →
- LinkedLinked via unknownDecision-Aware Training for Sample-Based Generative Models →
- PossiblePossibly related (embedding) · 55%modelplaneai/modelplane →
- PossiblePossibly related (embedding) · 48%benjaminzwhite/reasoning-models →
- PossiblePossibly related (embedding) · 48%edwardcapriolo/deliverance →
- PossiblePossibly related (embedding) · 52%trymirai/uzu →
- PossiblePossibly related (embedding) · 48%shap/shap →
- PossiblePossibly related (embedding) · 51%amitshekhariitbhu/llm-internals →
Related to (incoming)
paperReliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific ModelspaperDecision-Aware Training for Sample-Based Generative Modelsrepomodelplaneai/modelplanerepobenjaminzwhite/reasoning-modelsrepoedwardcapriolo/deliverancerepotrymirai/uzureposhap/shaprepoamitshekhariitbhu/llm-internalspaperSteering Neural Network Training through Interpretable Constraints Based on Partial Dependence
Related across the graph
paperSteering Neural Network Training through Interpretable Constraints Based on Partial Dependencereposhap/shaprepoamitshekhariitbhu/llm-internalsrepomodelplaneai/modelplanerepoedwardcapriolo/deliverancerepobenjaminzwhite/reasoning-modelsrepotrymirai/uzupaperDecision-Aware Training for Sample-Based Generative ModelspaperReliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models