23 citations · 32 across the 12 of their papers we have counts for
5 papers · 1 filter
Selective Inference for Clustering Under Unknown Covariance
Yiqun T. Chen, Lucy L. Gao
Unsupervised clustering is widely used to discover underlying group structure, after which researchers often seek to validate these groups via post-hoc hypothesis testing on the po…
InferenceEvolve: Towards Automated Causal Effect Estimators through Self-Evolving AI
Can Wang, Hongyu Zhao, Yiqun Chen
Causal inference is central to scientific discovery, yet choosing appropriate methods remains challenging because of the complexity of both statistical methodology and real-world d…
Power Analysis for Prediction-Powered Inference
Yiqun T. Chen, Moran Guo, Shengy Li
Modern studies increasingly leverage outcomes predicted by machine learning and artificial intelligence (AI/ML) models, and recent work, such as prediction-powered inference (PPI),…
Personalized Prediction of Perceived Message Effectiveness Using Large Language Model Based Digital Twins
Jasmin Han, Janardan Devkota, Joseph Waring +8
Perceived message effectiveness (PME) by potential intervention end-users is important for selecting and optimizing personalized smoking cessation intervention messages for mobile…
Efficient Inference for Noisy LLM-as-a-Judge Evaluation
Yiqun T Chen, Sizhu Lu, Sijia Li +2
Large language models (LLMs) are increasingly used as automatic evaluators of generative AI outputs, a paradigm often referred to as "LLM-as-a-judge." In practice, LLM judges are i…