10 papers
Simultaneous Inference for Centre-Outward Rankings of Random Objects
Lingfeng Lyu, Doudou Zhou
In many applications one object is chosen to represent a sample and the least typical objects are set aside, usually without any measure of uncertainty. We measure how central an o…
AgentCue: Statistical Summaries for Guiding Decentralized Multi-Agent Self-Organization
Guojun Zhu, Xinyou Chen, Kejian Zhang +2
Multi-agent systems (MAS) combine multiple agents to solve complex tasks, and recent MAS scale to more than a thousand agents. At this scale, decentralized MAS remove the central o…
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…
Conditional Evaluation of Language Models with Cheap Auxiliary Signals
Zhi Zhang, Lingfeng Lyu, Yue Kang +1
Aggregate accuracy hides where models succeed and fail. Estimating conditional performance profiles from gold labels alone is expensive, while cheap auxiliary signals such as LLM-j…
Pattern-Calibrated Multimodal Prediction under Blockwise Missingness
Junhan Yu, Kejian Zhang, Doudou Zhou +1
Blockwise missingness in multimodal data is usually treated as an incomplete-input problem. We instead focus on prediction for a prespecified observed-modality pattern, where the o…
Preference-based Centrality and Ranking in General Metric Spaces
Lingfeng Lyu, Doudou Zhou
Ranking or assessing centrality in multivariate and non-Euclidean data is difficult because there is no canonical order and many depth notions become computationally fragile in hig…
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…
From Hawkes Processes to Attention: Time-Modulated Mechanisms for Event Sequences
Xinzi Tan, Kejian Zhang, Junhan Yu +1
Marked Temporal Point Processes (MTPPs) arise naturally in medical, social, commercial, and financial domains. However, existing Transformer-based methods mostly inject temporal in…
Two-sample Testing with Block-wise Missingness in Multi-source Data
Kejian Zhang, Muxuan Liang, Robert Maile +1
Multi-source and multi-modal datasets are increasingly common in scientific research, yet they often exhibit block-wise missingness, where entire modalities are systematically abse…
MATES: Multi-view Aggregated Two-Sample Test
Zexi Cai, Wenbo Fei, Doudou Zhou
The two-sample test is a fundamental problem in statistics with a wide range of applications. In the realm of high-dimensional data, nonparametric methods have gained prominence du…