Personalized image generation aims to synthesize target images tailored to individual preferences based on users’ historical interaction data. Existing methods typically inject features from historical interaction records to guide personalized generation. However, such methods encounter two critical challenges when ser...
Yu-Ting Zhang, Ying Sun, Da-Zhong Shen et al.· Proceedings of the 20th ACM...· 0 citations
The proposed PRIME (Potential Robust Integrated Macro Energy), a framework that grounds return generation and tail-risk control in energy-based modeling and game theory from a momentum perspective, achieves approximately 10% improvement over state-of-the-art baselines with theoretical guarantees on convergence and rank...
Junren Xiao, Ruiyao Miao, Zixuan Yuan et al.· Proceedings of the 32nd ACM...· 0 citations
This work proposes CEDAR (Controlled and Event-Driven Demand forecasting via Action-aware Residual decomposition), a two-stage framework for robust decision-conditioned simulation that consistently improves simulation accuracy over strong TSF baselines and delivers practical gains for real-world budget planning.
Jun-Jie Meng, Ran Zhang, Zi-An Zhang et al.· Proceedings of the 32nd ACM...· 1 citation· ⚡1
Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning : merchants need to evaluate sales outcomes under future action sequences such as budget schedules, rather than passively predicting what happens next. However, most existing time series forecasting (TSF) approaches remain i...
Junjie Meng, Ran Zhang, Zi-An Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
While AI agents delivered highly efficient, directionally aligned assessments, they did not fully capture the nuances of human clinical judgment and could not substitute for physician-centered evaluation and promise assistive tools that can triage or pre-screen outputs to reduce human burden.
Peilun Shi, Jian Li, Ziqi Yang et al.· npj Digital Medicine· 0 citations
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