3 accepted papers
As large language models (LLMs) are increasingly deployed in real-world systems, they must support post-hoc removal of specific content to meet privacy and governance requirements. This motivates selective unlearning, which suppresses information about a particular entity or topic while preserving t…
Detecting fraudulent online text is essential, as these manipulative messages exploit human greed, deceive individuals, and endanger societal security. Currently, this task remains under-explored on the Chinese web due to the lack of a comprehensive dataset of Chinese fraudulent texts. However, crea…
The increase in computing power and the necessity of AI-assisted decision-making boost the growing application of large language models (LLMs). Along with this, the potential retention of sensitive data of LLMs has spurred increasing research into machine unlearning. However, existing unlearning app…