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Weikai Lu

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Articles

SDD: Self-Degraded Defense against Malicious Fine-tuning

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By Weikai Lu, Xin Lin, Ziqian Zeng
| arXiv
arXiv:2507.21182 (cs) View PDF HTML (experimental) Comments: Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) Cite as: arXiv:2507.21182 [cs.CR] (or arXiv:2507.21182v1 [cs.CR] for this version) https://doi.org/10.48550/arXiv.2507.21182 Submission history From: Chen Zixuan [ view email] [v1] Sun, 27 Jul 2025 02:08:21 UTC (765 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Connected Papers Toggle Connected Papers (What is Connected...
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Graph-Guided Neural Network for Tourism Demand Forecasting

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By Jinlong Cheng, Jijie Fan, Weikai Lu, Satyvaldieva Baktygul Abduraimovna
| IEEE
The experimental results of five methods on the HK-2018 and MO-2018 datasets are presented in Table 2 and Table 3. As we can see, the GTDFN shows the best performance in all metrics and all datasets. Particularly, on the HK-2018 dataset, the GTDFN outperforms the best baseline at the term of MAPE by 18.70% when the prediction horizon is 1. On the MO-2018 dataset, the performance of GTDFN is 22.10% better than the best baseline at the term of RMSE when the prediction horizon is 1.
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