5 citations · 20 across the 31 of their papers we have counts for
6 papers · 1 filter
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection
Sihan Chen, Zhuangzhuang Qian, Wingchun Siu +10
Outlier detection (OD), also known as anomaly detection, is a critical machine learning (ML) task with applications in fraud detection, network intrusion detection, clickstream ana…
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…
DPU: Dynamic Prototype Updating for Multimodal Out-of-Distribution Detection
Shawn Li, Huixian Gong, Hao Dong +3
Out-of-distribution (OOD) detection is essential for ensuring the robustness of machine learning models by identifying samples that deviate from the training distribution. While tr…
CMOOD: Concept-based Multi-label OOD Detection
Zhendong Liu, Yi Nian, Yuehan Qin +4
How can models effectively detect out-of-distribution (OOD) samples in complex, multi-label settings without extensive retraining? Existing OOD detection methods struggle to captur…
TVR-Ranking: A Dataset for Ranked Video Moment Retrieval with Imprecise Queries
Renjie Liang, Li Li, Chongzhi Zhang +3
In this paper, we propose the task of \textit{Ranked Video Moment Retrieval} (RVMR) to locate a ranked list of matching moments from a collection of videos, through queries in natu…
Backpropagation-Free Multi-modal On-Device Model Adaptation via Cloud-Device Collaboration
Wei Ji, Li Li, Zheqi Lv +5
In our increasingly interconnected world, where intelligent devices continually amass copious personalized multi-modal data, a pressing need arises to deliver high-quality, persona…