1 citations · 1 across the 8 of their papers we have counts for
9 papers
DACP: A Scientific Data Access and Collaboration Protocol
Zhihong Shen, Xiaojie Zhu, Zhenjing Cheng +3
Scientific computing is rapidly entering a data-intensive era. However, existing general-purpose network protocol stacks face limitations in eliminating data silos and improving da…
Forgetting to Witness: Efficient Federated Unlearning and Its Visible Evaluation
Houzhe Wang, Xiaojie Zhu, Chi Chen
With the increasing importance of data privacy and security, federated unlearning has emerged as a novel research field dedicated to ensuring that federated learning models no long…
Jellyfish: Zero-Shot Federated Unlearning Scheme with Knowledge Disentanglement
Houzhe Wang, Xiaojie Zhu, Chi Chen
With the increasing importance of data privacy and security, federated unlearning emerges as a new research field dedicated to ensuring that once specific data is deleted, federate…
ALT4Decompile: Inferring C-aligned Abstract Loop Tree for LLM-Based Binary Decompilation
Yongpan Wang, Puzhuo Liu, Xin Xu +4
Decompilation refers to the process of recovering high-level (C) language code from low-level (assembly) code. Recent Large Language Model (LLM)-based methods can generate re-execu…
BinEnhance: An Enhancement Framework Based on External Environment Semantics for Binary Code Search
Yongpan Wang, Hong Li, Xiaojie Zhu +4
Binary code search plays a crucial role in applications like software reuse detection. Currently, existing models are typically based on either internal code semantics or a combina…
Goldfish: An Efficient Federated Unlearning Framework
Houzhe Wang, Xiaojie Zhu, Chi Chen +1
With recent legislation on the right to be forgotten, machine unlearning has emerged as a crucial research area. It facilitates the removal of a user's data from federated trained…