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counterfactual

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Showing 1551–1575 of 2765 papers

TitleStatusHype
Towards Two-Stage Counterfactual Learning to Rank—0
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization—0
Towards Understanding Linear Value Decomposition in Cooperative Multi-Agent Q-Learning—0
TRACE: A Self-Improving Framework for Robot Behavior Forecasting with Vision-Language Models—0
Training and Validating a Treatment Recommender with Partial Verification Evidence—0
Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four—0
Training Data Attribution via Approximate Unrolled Differentiation—0
Training on Plausible Counterfactuals Removes Spurious Correlations—0
Transcending XAI Algorithm Boundaries through End-User-Inspired Design—0
Transdisciplinary AI Observatory -- Retrospective Analyses and Future-Oriented Contradistinctions—0
Transferable Fairness for Cold-Start Recommendation—0
Transfer learning with causal counterfactual reasoning in Decision Transformers—0
Translational Lung Imaging Analysis Through Disentangled Representations—0
Transmission Benefits and Cost Allocation under Ambiguity—0
Transparent AI: Developing an Explainable Interface for Predicting Postoperative Complications—0
Treatment Effects in Bunching Designs: The Impact of Mandatory Overtime Pay on Hours—0
Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions—0
Tree-based Synthetic Control Methods: Consequences of moving the US Embassy—0
Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation—0
Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning—0
Trustless Audits without Revealing Data or Models—0
Trustworthy Actionable Perturbations—0
Truth or Twist? Optimal Model Selection for Reliable Label Flipping Evaluation in LLM-based Counterfactuals—0
Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound—0
Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation—0
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