3 papers
stat.ML2026
Estimating Heterogeneous Causal Effect on Networks via Orthogonal Learning
Yuanchen Wu, Yubai Yuan
Estimating causal effects on networks is challenging because treatments may affect both treated units and their neighbors, while network homophily induces dependence and confoundin…
cs.CL2026
LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization
Yuanchen Wu, Saurabh Verma, Justin Lee +6
Large language models (LLMs) are highly sensitive to prompts, but most automatic prompt optimization (APO) methods assume access to ground-truth references (e.g., labeled validatio…
stat.ML2024
Robust Offline Active Learning on Graphs
Yuanchen Wu, Yubai Yuan
We consider the problem of active learning on graphs, which has crucial applications in many real-world networks where labeling node responses is expensive. In this paper, we propo…