5 citations · 10 across the 7 of their papers we have counts for
7 papers
Generative Optimization for Incentivized Advertising with Global Level Constraints
Gege Chen, Ning Luo, Hao Jiang +7
Incentivized advertising allocates monetary or virtual rewards to drive user engagement, where a key challenge is optimizing continuous incentive magnitudes under strict global con…
Why Self-Inconsistency Arises in GNN Explanations and How to Exploit It
Wenxin Tai, Yaqian Liu, Ting Zhong +1
Recent work has observed that explanations produced by Self-Interpretable Graph Neural Networks (SI-GNNs) can be self-inconsistent: when the model is reapplied to its own explanato…
Compose Yourself: Average-Velocity Flow Matching for One-Step Speech Enhancement
Gang Yang, Yue Lei, Wenxin Tai +4
Diffusion and flow matching (FM) models have achieved remarkable progress in speech enhancement (SE), yet their dependence on multi-step generation is computationally expensive and…
Analyzing and Mitigating Repetitions in Trip Recommendation
Wenzheng Shu, Kangqi Xu, Wenxin Tai +3
Trip recommendation has emerged as a highly sought-after service over the past decade. Although current studies significantly understand human intention consistency, they struggle…
Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection
Chunjing Xiao, Shikang Pang, Wenxin Tai +3
Graph-level anomaly detection is significant in diverse domains. To improve detection performance, counterfactual graphs have been exploited to benefit the generalization capacity…
End-to-End High Accuracy License Plate Recognition Based on Depthwise Separable Convolution Networks
Song-Ren Wang, Hong-Yang Shih, Zheng-Yi Shen +1
Automatic license plate recognition plays a crucial role in modern transportation systems such as for traffic monitoring and vehicle violation detection. In real-world scenarios, l…
Foster Strengths and Circumvent Weaknesses: a Speech Enhancement Framework with Two-branch Collaborative Learning
Wenxin Tai, Jiajia Li, Yixiang Wang +2
Recent single-channel speech enhancement methods usually convert waveform to the time-frequency domain and use magnitude/complex spectrum as the optimizing target. However, both ma…