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cs.LG2026
Decision-Weighted Flow Matching for Contextual Stochastic Optimization
Jize Xie, Haomiao Wu, Qiang Chen +2
Conditional generative models are increasingly used as scenario generators for stochastic optimization, but standard training objectives emphasize uniform distributional fit rather…
cs.LG2026
Detect by Yourself: Self-Designing Agentic Workflows for Few-Shot Graph Anomaly Detection
Tairan Huang, Qiang Chen, Yili Wang +4
Graph anomaly detection aims to identify anomaly nodes in attributed graphs and plays an important role in real-world applications. However, existing graph anomaly detection method…
cs.LG2026
LEGATO: Good Identity Unlearning Is Continuous
Qiang Chen, Chun-Wun Cheng, Xiu Su +5
Machine unlearning has become a crucial role in enabling generative models trained on large datasets to remove sensitive, private, or copyright-protected data. However, existing ma…