449 citations · 1k across the 8 of their papers we have counts for
8 papers
A Large-Scale Simulation on Large Language Models for Decision-Making in Political Science
Chenxiao Yu, Jinyi Ye, Yuangang Li +4
While LLMs have demonstrated remarkable capabilities in text generation and reasoning, their ability to simulate human decision-making -- particularly in political contexts -- rema…
Towards More Accurate US Presidential Election via Multi-step Reasoning with Large Language Models
Chenxiao Yu, Zhaotian Weng, Yuangang Li +3
Can Large Language Models (LLMs) accurately predict election outcomes? While LLMs have demonstrated impressive performance in various domains, including healthcare, legal analysis,…
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions
Zheng Li, Yue Zhao, Xiyang Hu +3
Outlier detection refers to the identification of data points that deviate from a general data distribution. Existing unsupervised approaches often suffer from high computational c…
SYNC: A Copula based Framework for Generating Synthetic Data from Aggregated Sources
Zheng Li, Yue Zhao, Jialin Fu
A synthetic dataset is a data object that is generated programmatically, and it may be valuable to creating a single dataset from multiple sources when direct collection is difficu…
COPOD: Copula-Based Outlier Detection
Zheng Li, Yue Zhao, Nicola Botta +2
Outlier detection refers to the identification of rare items that are deviant from the general data distribution. Existing approaches suffer from high computational complexity, low…
SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula
Colin Wan, Zheng Li, Alicia Guo +1
Synthetic population generation is the process of combining multiple socioeconomic and demographic datasets from different sources and/or granularity levels, and downscaling them t…
LSCP: Locally Selective Combination in Parallel Outlier Ensembles
Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki +1
In unsupervised outlier ensembles, the absence of ground truth makes the combination of base outlier detectors a challenging task. Specifically, existing parallel outlier ensembles…
PyOD: A Python Toolbox for Scalable Outlier Detection
Yue Zhao, Zain Nasrullah, Zheng Li
PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data. Uniquely, it provides access to a wide range of outlier detection algorithms,…