activity
20202026
most citedECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions

449 citations · 985 across the 27 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

Cloud-ScPO: Hidden-State Geometry for Semi-Supervised Preference Optimization in LLM Reasoning

Yuzhou Liu, Xiyang Hu

Preference optimization improves mathematical reasoning in large language models (LLMs), but reliable chosen-rejected pairs usually require verified answers, human annotations, or…

cs.CL2025

Mitigating Hallucinations in Large Language Models via Causal Reasoning

Yuangang Li, Yiqing Shen, Yi Nian +7

Large language models (LLMs) exhibit logically inconsistent hallucinations that appear coherent yet violate reasoning principles, with recent research suggesting an inverse relatio…

cs.CL2025

A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations

Li Li, Peilin Cai, Ryan A. Rossi +21

We present PersonaConvBench, a large-scale benchmark for evaluating personalized reasoning and generation in multi-turn conversations with large language models (LLMs). Unlike exis…

cs.CL2025

AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection

Tiankai Yang, Junjun Liu, Wingchun Siu +6

Anomaly detection (AD) is essential in areas such as fraud detection, network monitoring, and scientific research. However, the diversity of data modalities and the increasing numb…

cs.CL2024★ 2 cited

Political-LLM: Large Language Models in Political Science

Lincan Li, Jiaqi Li, Catherine Chen +44

In recent years, large language models (LLMs) have been widely adopted in political science tasks such as election prediction, sentiment analysis, policy impact assessment, and mis…

cs.CL2024

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…

cs.CL2024★ 3 cited

AD-LLM: Benchmarking Large Language Models for Anomaly Detection

Tiankai Yang, Yi Nian, Shawn Li +9

Anomaly detection (AD) is an important machine learning task with many real-world uses, including fraud detection, medical diagnosis, and industrial monitoring. Within natural lang…

cs.CL2024

NLP-ADBench: NLP Anomaly Detection Benchmark

Yuangang Li, Jiaqi Li, Zhuo Xiao +4

Anomaly detection (AD) is an important machine learning task with applications in fraud detection, content moderation, and user behavior analysis. However, AD is relatively underst…