3 papers
math.ST2026
Human-Anchored Inference for Ranking New Models with Large Language Model Judges
Xin Zhou, Sinian Zhang, Zhanyan Yang +3
Human pairwise comparisons provide a reference for evaluating large language models (LLMs), but collecting sufficient judgments for each new release is costly and time-consuming. L…
stat.ME2026
Learning Sequential Decisions from Multiple Sources via Group-Robust Markov Decision Processes
Mingyuan Xu, Zongqi Xia, Tianxi Cai +2
Learning a common policy from multiple source environments requires accounting for cross-source heterogeneity, and the offline setting introduces an additional challenge of limited…
stat.ML2026
A Judge-Aware Ranking Framework for Evaluating Large Language Models without Ground Truth
Mingyuan Xu, Xinzi Tan, Jiawei Wu +1
Evaluating large language models (LLMs) on open-ended tasks without ground-truth labels is increasingly done via the LLM-as-a-judge paradigm. A critical but under-modeled issue is…