5 papers
Everywhere Valid Bounds on False Discovery Proportions in Conformal Inference
Ziang Song, Ying Jin, Emmanuel J. Candès
Modern applications of conformal inference to multiple testing problems, such as outlier detection and candidate selection, often involve selecting test samples whose conformal p-v…
Optimized Labeling Resource Allocation for Prediction-Assisted Inference via OPAL
Virginia L. Ma, Emmanuel J. Candès
Active Statistical Inference is a new framework to make precise claims about population parameters with provable statistical guarantees. It uses a predictive "black-box" machine le…
FUSE: Ensembling Verifiers with Zero Labeled Data
Joonhyuk Lee, Virginia Ma, Sarah Zhao +4
Verification of model outputs is rapidly emerging as a key primitive for both training and real-world deployment of large language models (LLMs). In practice, this often involves u…
Diversifying Conformal Selections
Yash Nair, Ying Jin, James Yang +1
When selecting from a list of potential candidates, it is important to ensure not only that the selected items are of high quality, but also that they are sufficiently dissimilar s…
Automated Hypothesis Validation with Agentic Sequential Falsifications
Kexin Huang, Ying Jin, Ryan Li +3
Hypotheses are central to information acquisition, decision-making, and discovery. However, many real-world hypotheses are abstract, high-level statements that are difficult to val…