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TitleStatusHype
Counterfactual Formulation of Patient-Specific Root Causes of Disease—0
CFGs: Causality Constrained Counterfactual Explanations using goal-directed ASP—0
CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems—0
A Survey of the Various Methodologies Towards making Artificial Intelligence More Explainable—0
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder—0
CETransformer: Casual Effect Estimation via Transformer Based Representation Learning—0
Ceteris paribus logic in counterfactual reasoning—0
CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models—0
Does Misclassifying Non-confounding Covariates as Confounders Affect the Causal Inference within the Potential Outcomes Framework?—0
A Critical Review of Causal Reasoning Benchmarks for Large Language Models—0
Counterfactual Fairness through Transforming Data Orthogonal to Bias—0
Counterfactual Fairness with Partially Known Causal Graph—0
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals—0
Center of Gravity-Guided Focusing Influence Mechanism for Multi-Agent Reinforcement Learning—0
A bounded rationality account of dependency length minimization in Hindi—0
CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines—0
Counterfactual Fairness Is Not Demographic Parity, and Other Observations—0
AgroXAI: Explainable AI-Driven Crop Recommendation System for Agriculture 4.0—0
Counterfactual Fairness in Text Classification through Robustness—0
CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification—0
Causes of Effects: Learning individual responses from population data—0
A statistical model for aggregating judgments by incorporating peer predictions—0
Counterfactual Fairness Is Basically Demographic Parity—0
Counterfactual fairness: removing direct effects through regularization—0
CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation—0
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