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Found 4 papers, 2 papers with code
Causality for Large Language Models
How to embed causality into the training process of LLMs and build more general and intelligent models remains unexplored.
IntOPE: Off-Policy Evaluation in the Presence of Interference
Off-Policy Evaluation (OPE) is employed to assess the potential impact of a hypothetical policy using logged contextual bandit feedback, which is crucial in areas such as personalized medicine and recommender systems, where online interactions are associated with significant risks and costs.
Causal Inference with Complex Treatments: A Survey
Causal inference plays an important role in explanatory analysis and decision making across various fields like statistics, marketing, health care, and education.
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation
Estimating the individuals' potential response to varying treatment doses is crucial for decision-making in areas such as precision medicine and management science.
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