Manifold-Aligned Rectification Flow is proposed, a flow matching based framework that explicitly rectifies noisy social representations toward preference-aligned embeddings and effectively bridges the gap between the social and preference domains, yielding robust and discriminative user representations.
Qing Meng, Zhu-Fu Song, Huiyu Min et al.· Proceedings of the Thirty-Fi...· 0 citations
Safeguarding smart contracts is paramount to the security of the blockchain ecosystem. In recent years, numerous studies have employed deep learning techniques to detect vulnerabilities in smart contracts based on their bytecode. However, such approaches are primarily limited by inherent code redundancy and coarse-grai...
Jia-Ying Xie, Yan-Xiang Tong, Xiao Wang et al.· Annual International Compute...· 0 citations
As a core technology in blockchain-based systems, smart contracts are widely used in various fields. Meanwhile, their post-deployment immutability and financial nature render vulnerabilities attractive to attackers, as evidenced by significant economic losses, making smart contract vulnerability detection a critical ta...
Yunhan Zhang, Yan-Xiang Tong, Ben Wang et al.· Annual International Compute...· 0 citations
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