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20232025
most citedPrompting Video-Language Foundation Models with Domain-specific Fine-grained Heuristics for Video Question Answering

9 citations · 24 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.LG2023

ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection

Junwei He, Qianqian Xu, Yangbangyan Jiang +2

Graph anomaly detection is crucial for identifying nodes that deviate from regular behavior within graphs, benefiting various domains such as fraud detection and social network. Al…

cs.LG2023

DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework

Siran Dai, Qianqian Xu, Zhiyong Yang +2

The Area Under the ROC Curve (AUC) is a widely employed metric in long-tailed classification scenarios. Nevertheless, most existing methods primarily assume that training and testi…

cs.LG2023

Towards Demystifying the Generalization Behaviors When Neural Collapse Emerges

Peifeng Gao, Qianqian Xu, Yibo Yang +5

Neural Collapse (NC) is a well-known phenomenon of deep neural networks in the terminal phase of training (TPT). It is characterized by the collapse of features and classifier into…

cs.LG2023★ 3 cited

A Unified Perspective for Loss-Oriented Imbalanced Learning via Localization

Zitai Wang, Qianqian Xu, Zhiyong Yang +4

Due to the inherent imbalance in real-world datasets, naïve Empirical Risk Minimization (ERM) tends to bias the learning process towards the majority classes, hindering generalizat…

cs.CV2023

When Measures are Unreliable: Imperceptible Adversarial Perturbations toward Top- Multi-Label Learning

Yuchen Sun, Qianqian Xu, Zitai Wang +1

With the great success of deep neural networks, adversarial learning has received widespread attention in various studies, ranging from multi-class learning to multi-label learning…