4 papers
MechMath: Sorrifier-Driven Formal Decomposition Workflow for Automated Theorem Proving
Ruichen Qiu, Yichuan Cao, Junqi Liu +4
Recent advances in large language models (LLMs) and LLM-based agents have substantially improved the capabilities of automated theorem proving. However, for problems that require c…
A Survey on Unlearning in Large Language Models
Ruichen Qiu, Jiajun Tan, Jiayue Pu +3
Large Language Models (LLMs) demonstrate remarkable capabilities, but their training on massive corpora poses significant risks from memorized sensitive information. To mitigate th…
MUC: Machine Unlearning for Contrastive Learning with Black-box Evaluation
Yihan Wang, Yiwei Lu, Guojun Zhang +4
Machine unlearning offers effective solutions for revoking the influence of specific training data on pre-trained model parameters. While existing approaches address unlearning for…
BridgePure: Limited Protection Leakage Can Break Black-Box Data Protection
Yihan Wang, Yiwei Lu, Xiao-Shan Gao +2
Availability attacks, or unlearnable examples, are defensive techniques that allow data owners to modify their datasets in ways that prevent unauthorized machine learning models fr…