causal inference 1heterogeneous treatment effect 1large language models 1representation learning 1uncertainty guidance 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation
Jialu Xu, Mengkun Liang, Guannan Liu +2
The paper introduces CURL, a method that uses uncertainty estimates to guide a frozen large language model in creating semantic representations for covariates, improving heterogene…
cs.AI2026
Quark Medical Alignment: A Holistic Multi-Dimensional Alignment and Collaborative Optimization Paradigm
Tianxiang Xu, Jiayi Liu, Yixuan Tong +10
While reinforcement learning for large language model alignment has progressed rapidly in recent years, transferring these paradigms to high-stakes medical question answering revea…
cs.LG2026
We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification
Zhipeng Liu, Peibo Duan, Xuan Tang +6
The World Wide Web thrives on intelligent services that rely on accurate time series classification, which has recently witnessed significant progress driven by advances in deep le…