2 citations · 2 across the 6 of their papers we have counts for
16 papers
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…
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…
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…
StealthRank: LLM Ranking Manipulation via Stealthy Prompt Optimization
Yiming Tang, Yi Fan, Chenxiao Yu +3
The integration of large language models (LLMs) into information retrieval systems introduces new attack surfaces, particularly for adversarial ranking manipulations. We present $\…
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…
Graph Synthetic Out-of-Distribution Exposure with Large Language Models
Haoyan Xu, Zhengtao Yao, Ziyi Wang +4
Out-of-distribution (OOD) detection in graphs is critical for ensuring model robustness in open-world and safety-sensitive applications. Existing graph OOD detection approaches typ…