6 papers
AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network
Bolin Shen, Ziwei Huang, Zhiguang Cao +1
The Traveling Salesman Problem (TSP) is a cornerstone of combinatorial optimization and arises in many practical scenarios. Although graph-based learning approaches have been explo…
From Competition to Synergy: Unlocking Reinforcement Learning for Subject-Driven Image Generation
Ziwei Huang, Ying Shu, Hao Fang +5
Subject-driven image generation models face a fundamental trade-off between identity preservation (fidelity) and prompt adherence (editability). While online reinforcement learning…
RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
Hang Yi, Ziwei Huang, Yining Ma +1
Recent neural solvers have achieved strong performance on vehicle routing problems (VRPs), yet they mainly assume symmetric Euclidean distances, restricting applicability to real-w…
PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing
Xiaoshan Yu, Ziwei Huang, Shangshang Yang +3
With the rapid advancement of intelligent education, Computerized Adaptive Testing (CAT) has attracted increasing attention by integrating educational psychology with deep learning…
TBStar-Edit: From Image Editing Pattern Shifting to Consistency Enhancement
Hao Fang, Zechao Zhan, Weixin Feng +3
Recent advances in image generation and editing technologies have enabled state-of-the-art models to achieve impressive results in general domains. However, when applied to e-comme…
Rethinking Light Decoder-based Solvers for Vehicle Routing Problems
Ziwei Huang, Jianan Zhou, Zhiguang Cao +1
Light decoder-based solvers have gained popularity for solving vehicle routing problems (VRPs) due to their efficiency and ease of integration with reinforcement learning algorithm…